gym-anm
is a framework for designing reinforcement learning (RL) environments that model Active Network
Management (ANM) tasks in electricity distribution networks. It is built on top of the
OpenAI Gym toolkit.
The gym-anm
framework was designed with one goal in mind: bridge the gap between research in RL and in
the management of power systems. We attempt to do this by providing RL researchers with an easy-to-work-with
library of environments that model decision-making tasks in power grids.
Papers: