A Multi-agent Deep Reinforcement Learning Based Voltage Regulation using Coordinated PV Inverters

Di Cao, Weihao Hu, Junbo Zhao, Qi Huang, Zhe Chen, Frede Blaabjerg

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Abstract

This paper proposes a multi-Agent deep reinforcement learning-based approach for distribution system voltage regulation with high penetration of photovoltaics (PVs). The designed agents can learn the coordinated control strategies from historical data through the counter-Training of local policy networks and centric critic networks. The learned strategies allow us to perform online coordinated control. Comparative results with other methods show the enhanced control capability of the proposed method under various conditions.

Original languageEnglish
Article number9113746
JournalI E E E Transactions on Power Electronics
Volume35
Issue number5
Pages (from-to)4120-4123
Number of pages4
ISSN0885-8993
DOIs
Publication statusE-pub ahead of print - Jun 2020

Keywords

  • voltage regulation
  • multi-agent deep reinforcement learning
  • coordinated control
  • Distributed system

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