Welcome to building-energy-storage-simulation’s documentation!

The Building Energy Storage Simulation serves as open source OpenAI gym (now gymnasium) environment for reinforcement learning. The environment represents a building with an energy storage (in form of a battery) and a solar energy system. The aim is to control the energy storage in such a way that the energy of the solar system can be used optimally.

A more detailed description of the task itself and the description of the markov decision process, containing information about the action space, observation space and reward can be found here.

Contents

API

Thanks To

The inspiration of this project and the data profiles come from the CityLearn environment. Anyhow, this project focuses on the ease of usage and the simplicity of its implementation.