Metadata-Version: 2.4
Name: softcpsrecsimulator
Version: 0.2.5
Summary: SoftCPS REC Simulator: an energy-community RL simulator fork focused on EV/BESS/PV, electrical-service constraints, and community-market experimentation.
Home-page: https://github.com/Soft-CPS-Research-Group/Simulator
Author: Soft-CPS Research Group, Jose Ramon Vazquez-Canteli, Kingsley Nweye, Zoltan Nagy
Author-email: jose@isep.ipp.pt
License: MIT
Project-URL: Source, https://github.com/Soft-CPS-Research-Group/Simulator
Project-URL: Original Project, https://github.com/intelligent-environments-lab/CityLearn
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.9
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License-File: LICENSE
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Requires-Dist: scikit-learn<=1.2.2
Requires-Dist: simplejson
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Requires-Dist: torchvision
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# SoftCPS REC Simulator

`softcpsrecsimulator` is a simulation framework maintained by the SoftCPS Research Group for
energy-community studies with reinforcement learning.

It is a fork-based project used for research and experimentation on:

- electric vehicles (EVs) and chargers,
- stationary batteries (BESS),
- photovoltaic generation (PV),
- electrical-service constraints (single/three-phase),
- local community market settlement and KPI analysis.

## Project Positioning

This package is a **fork project** built from the CityLearn codebase and extended for SoftCPS REC
simulation needs.

## Installation

```bash
pip install softcpsrecsimulator
```

## Python Usage

For compatibility with existing ecosystems, the Python module path currently remains:

```python
from citylearn.citylearn import CityLearnEnv
```

## Source and Documentation

- Source: https://github.com/Soft-CPS-Research-Group/Simulator
- Original upstream project: https://github.com/intelligent-environments-lab/CityLearn
