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Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm

Chao Zhu1, Lei Wang1, Dai Pan1, Zifei Wang2, Tao Wang2, Licheng Wang2,*, Chengjin Ye3

1 State Grid Zhejiang Economic and Technological Research Institute, Hangzhou, 310008, China
2 College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310023, China
3 College of Electrical Engineering, Zhejiang University, Hangzhou, 310058, China

* Corresponding Author: Licheng Wang. Email: email

(This article belongs to this Special Issue: Artificial Intelligence in Renewable Energy and Storage Systems)

Computer Modeling in Engineering & Sciences 2023, 134(1), 599-609.


In this paper, a model free volt/var control (VVC) algorithm is developed by using deep reinforcement learning (DRL). We transform the VVC problem of distribution networks into the network framework of PPO algorithm, in order to avoid directly solving a large-scale nonlinear optimization problem. We select photovoltaic inverters as agents to adjust system voltage in a distribution network, taking the reactive power output of inverters as action variables. An appropriate reward function is designed to guide the interaction between photovoltaic inverters and the distribution network environment. OPENDSS is used to output system node voltage and network loss. This method realizes the goal of optimal VVC in distribution network. The IEEE 13-bus three phase unbalanced distribution system is used to verify the effectiveness of the proposed algorithm. Simulation results demonstrate that the proposed method has excellent performance in voltage and reactive power regulation of a distribution network.


Cite This Article

Zhu, C., Wang, L., Pan, D., Wang, Z., Wang, T. et al. (2023). Research on Volt/Var Control of Distribution Networks Based on PPO Algorithm. CMES-Computer Modeling in Engineering & Sciences, 134(1), 599–609.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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