pymgrid: An Open-Source Python Microgrid Simulator for Applied Artificial Intelligence Research (Papers Track)

Gonzague Henri (Total); Tanguy Levent (Ecole Polytechnique); Avishai Halev (Total, UC Davis); Reda ALAMI (Total R&D); Philippe Cordier (Total S.A.)

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Power & Energy Reinforcement Learning


Microgrids – self-contained electrical grids that are capable of disconnecting from the main grid – hold potential in both tackling climate change mitigation via reducing CO$_2$ emissions and adaptation by increasing infrastructure resiliency. Due to their distributed nature, microgrids are often idiosyncratic; as a result, control of these systems is nontrivial. While microgrid simulators exist, many are limited in scope and in the variety of microgrids they can simulate. We propose \HL{pymgrid}, an open-source Python package to generate and simulate a large number of microgrids, and the first open-source tool that can generate more than 600 different microgrids. \HL{pymgrid} abstracts most of the domain expertise, allowing users to focus on control algorithms. In particular, \HL{pymgrid} is built to be a reinforcement learning (RL) platform, and includes the ability to model microgrids as Markov decision processes. \HL{pymgrid} also introduces two pre-computed list of microgrids, intended to allow for research reproducibility in the microgrid setting.

Recorded Talk (direct link)