A framework for running reinforcement learning experiments on energy environments - starting with electric battery storage.

• Electric battery storage environment for energy arbitrage
• Integration with Gymnasium as a custom Gymnasium environment
• Integration with Stable Baselines 3 for reinforcement learning agents
• Historical electricity price data for realistic training scenarios
• Experiment framework for training and evaluation on separate datasets
• Tensorboard logging for experiment tracking

$ make setup

$ uv run examples/battery.py

Or run a more extensive experiment with real electricity price data:

$ uv run examples/battery_arbitrage_experiments.py

$ make test