Proximal Policy Optimization for Volt-VAR Control in Distribution Networks with Renewable Energy Resources

• Published in: 2021 IEEE Sustainable Power and Energy Conference (iSPEC) pp. 677 - 681
• Main Authors: Zhu, Tao, Hai, Di, Zhou, Shengchao, Zhang, Ruiying, Yan, Ziheng, Wu, Minghe
• Format: Conference Proceeding
• Language: English
• Published: IEEE 23.12.2021
• Subjects: Costs; deep reinforcement learning; Markov decision process; policy gradient methods; Power systems; Process control; Propagation losses; Reinforcement learning; Renewable energy sources; Training; Volt/VAR control

This paper addresses the problem of Volt/VAR control (VVC), which becomes a critical issue with the increasing renewable energy resources integration in power distribution networks. Traditional methods are limited due to the incomplete measurements in such scenarios. Recently, deep reinforcement lea...