Explicit demand response peak load

[Manish-Khanra]

Pull Request

Related Issue

Closes #[issue number] (if applicable)

Description

Changes Proposed

Implementation of Flexibility Measures:

1. Cost-Based Load Shifting: Optimize operations to minimize variable costs while considering load-shifting capabilities.
2. Congestion Management Flexibility: Adjust operations based on grid congestion signals to reduce congestion at critical nodes.
3. Peak Load Shifting: Curtail demand during peak load periods to adhere to capacity constraints and improve grid stability.
4. Renewable Utilisation: Align operational load increases with renewable energy availability to enhance grid sustainability.
5. Deprecated indexing warnings for pd.Series and replaced with .iloc.

Testing

Individual test fixtures for each flexibility measure.

Checklist

Please check all applicable items:

• Code changes are sufficiently documented (docstrings, inline comments, doc folder updates)
• New unit tests added for new features or bug fixes
• Existing tests pass with the changes
• Reinforcement learning examples are operational (for DRL-related changes)
• Code tested with both local and Docker databases
• Code follows project style guidelines and best practices
• Changes are backwards compatible, or deprecation notices added
• New dependencies added to pyproject.toml
• A note for the release notes doc/release_notes.rst of the upcoming release is included
• Consent to release this PR's code under the GNU Affero General Public License v3.0

Additional Notes (if applicable)

[Any additional information, concerns, or areas you want reviewers to focus on]

Screenshots (if applicable)

[Add screenshots to demonstrate visual changes]

[kim-mskw]

Discussion with @Manish-Khanra we used a big-M formulation to linearise the problem formulation. The second objective loop was reformulated to include the absolute values of the shift; otherwise, the objective value was forced to 0 due to the demand covering constraint, which led to arbitrary solutions.

Note that there are no costs included in the second objective loop, leading to multiple possible solutions with the same absolute load shift that does not violate the cost increase constraints. Hence, different solvers will most likely result in different solutions.

[codecov]

Codecov Report

Attention: Patch coverage is 91.53846% with 22 lines in your changes missing coverage. Please review.

Project coverage is 78.01%. Comparing base (cdaf49f) to head (e1e727b).
Report is 1 commits behind head on main.

Files with missing lines	Patch %	Lines
assume/units/dsm_load_shift.py	92.65%	13 Missing ⚠️
assume/common/forecasts.py	92.75%	5 Missing ⚠️
assume/strategies/naive_strategies.py	0.00%	3 Missing ⚠️
assume/units/hydrogen_plant.py	66.66%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #484      +/-   ##
==========================================
+ Coverage   77.52%   78.01%   +0.49%     
==========================================
  Files          50       50              
  Lines        6812     6938     +126     
==========================================
+ Hits         5281     5413     +132     
+ Misses       1531     1525       -6     

Flag	Coverage Δ
pytest	78.01% <91.53%> (+0.49%)	⬆️

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[nick-harder]

@Manish-Khanra I have fixed several things and streamlined the code. Everything is fine, but there are some things you should address before we can merge this into main

[nick-harder]

@Manish-Khanra also please complete the PR form above