pymgrid: An Open-Source Python Microgrid Simulator for Applied Artificial Intelligence Research
This tool addresses the need for reproducible and accessible simulation platforms for applied AI research in microgrid control, which is incremental as it builds on existing simulators but offers greater variety and openness.
The authors tackled the problem of limited and inflexible microgrid simulators by developing pymgrid, an open-source Python package that can generate and simulate over 600 different microgrids, abstracting domain expertise to focus on control algorithms like 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 CO2 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 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. pymgrid abstracts most of the domain expertise, allowing users to focus on control algorithms. In particular, pymgrid is built to be a reinforcement learning (RL) platform, and includes the ability to model microgrids as Markov decision processes. pymgrid also introduces two pre-computed list of microgrids, intended to allow for research reproducibility in the microgrid setting.