Computer Science > Machine Learning
[Submitted on 8 Sep 2021 (v1), last revised 14 Mar 2022 (this version, v3)]
Title:PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems
View PDFAbstract: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 \url{this https URL}.
Submission history
From: Ting-Han Fan [view email][v1] Wed, 8 Sep 2021 23:23:21 UTC (819 KB)
[v2] Mon, 20 Sep 2021 14:52:35 UTC (819 KB)
[v3] Mon, 14 Mar 2022 17:46:09 UTC (820 KB)
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