SOTAVerified

PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems

2021-09-08Code Available1· sign in to hype

Ting-Han Fan, Xian Yeow Lee, YuBo Wang

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

We introduce PowerGym, an open-source reinforcement learning environment for Volt-Var control in power distribution systems. Following OpenAI Gym APIs, PowerGym targets minimizing power loss and voltage violations under physical networked constraints. PowerGym provides four distribution systems (13Bus, 34Bus, 123Bus, and 8500Node) based on IEEE benchmark systems and design variants for various control difficulties. To foster generalization, PowerGym offers a detailed customization guide for users working with their distribution systems. As a demonstration, we examine state-of-the-art reinforcement learning algorithms in PowerGym and validate the environment by studying controller behaviors. The repository is available at https://github.com/siemens/powergym.

Tasks

Reproductions