Demand Response Optimization for Battery Energy Storage

[vijay092]

Demand Response Optimization for Battery Energy Storage (Stage 1)

This PR introduces a Pyomo-based formulation for demand response, which will be implemented in two stages.

As the first stage, this work implements a rolling horizon optimization for battery operations. The battery dispatch logic is based on a pre-defined signal, such as LMP, load, or a combination of both. This is the G&T level dispatch signal for demand response. The next stage will implement the peak load management logic.

Section 1: Type of Contribution

• Feature Enhancement
  • Framework
  • New Model
  • Updated Model
  • Tools/Utilities
  • Other (please describe):
• Bug Fix
• Documentation Update
• CI Changes
• Other (please describe):

Section 2: Draft PR Checklist

• Open draft PR
• Describe the feature that will be added
• Fill out TODO list steps
• Describe requested feedback from reviewers on draft PR
• Complete Section 7: New Model Checklist (if applicable)

TODO:

• Add unit tests
• Add documentation

Type of Reviewer Feedback Requested (on Draft PR)

Structural feedback: Is this in the right place?

Implementation feedback: I used the same style as Gen's pyomo implementation. Appreciate feedback here.

Other feedback:

Section 3: General PR Checklist

• PR description thoroughly describes the new feature, bug fix, etc.
• Added tests for new functionality or bug fixes
• Tests pass (If not, and this is expected, please elaborate in the Section 6: Test Results)
• Documentation
  • Docstrings are up-to-date
  • Related docs/ files are up-to-date, or added when necessary
  • Documentation has been rebuilt successfully
  • Examples have been updated (if applicable)
• CHANGELOG.md
  • At least one complete sentence has been provided to describe the changes made in this PR
  • After the above, a hyperlink has been provided to the PR using the following format:
    "A complete thought. [PR XYZ]((https://github.com/NatLabRockies/H2Integrate/pull/XYZ)", where
    XYZ should be replaced with the actual number.

Section 3: Related Issues

Section 4: Impacted Areas of the Software

Section 4.1: New Files

• Main Implementation: h2integrate/control/control_strategies/storage/plm_optimized_storage_controller.py

• Usage Example: examples/34_plm_optimized_dispatch

Section 4.2: Modified Files

• h2integrate/core/supported_models.py
  • Added the new model

Section 5: Additional Supporting Information

Section 6: Test Results, if applicable

Section 7 (Optional): New Model Checklist

• Model Structure:
  • Follows established naming conventions outlined in docs/developer_guide/coding_guidelines.md
  • Used attrs class to define the Config to load in attributes for the model
    • If applicable: inherit from BaseConfig or CostModelBaseConfig
  • Added: initialize() method, setup() method, compute() method
    • If applicable: inherit from CostModelBaseClass
• Integration: Model has been properly integrated into H2Integrate
  • Added to supported_models.py
  • If a new commodity_type is added, update create_financial_model in h2integrate_model.py
• Tests: Unit tests have been added for the new model
  • Pytest-style unit tests
  • Unit tests are in a "test" folder within the folder a new model was added to
  • If applicable add integration tests
• Example: If applicable, a working example demonstrating the new model has been created
  • Input file comments
  • Run file comments
  • Example has been tested and runs successfully in test_all_examples.py
• Documentation:
  • Write docstrings using the Google style
  • Model added to the main models list in docs/user_guide/model_overview.md
    • Model documentation page added to the appropriate docs/ section
    • <model_name>.md is added to the _toc.yml