LAPSE:2023.9148v1
Published Article
LAPSE:2023.9148v1
Secondary Voltage Collaborative Control of Distributed Energy System via Multi-Agent Reinforcement Learning
Tianhao Wang, Shiqian Ma, Na Xu, Tianchun Xiang, Xiaoyun Han, Chaoxu Mu, Yao Jin
February 27, 2023
Abstract
In this paper, a new voltage cooperative control strategy for a distributed power generation system is proposed based on the multi-agent advantage actor-critic (MA2C) algorithm, which realizes flexible management and effective control of distributed energy. The attentional actor-critic message processor (AACMP) is extended into the MA2C method to select the important messages from all communication messages adaptively and process important messages efficiently. The cooperative control strategy trained by centralized training and decentralized execution frame will take over the responsibility of the secondary control level for voltage restoration in a distributed manner. The introduction of the attention mechanism reduces the amount of information exchanged and the requirements of the communication network. Finally, a distributed system with six energy nodes is used to verify the effectiveness of the proposed control strategy.
Keywords
attentional mechanism, coordination optimization, deep reinforcement learning, distributed energy, nodal voltage
Suggested Citation
Wang T, Ma S, Xu N, Xiang T, Han X, Mu C, Jin Y. Secondary Voltage Collaborative Control of Distributed Energy System via Multi-Agent Reinforcement Learning. (2023). LAPSE:2023.9148v1
Author Affiliations
Wang T: Electric Power Research Institute, State Grid Tianjin Electric Power Company, No. 8, Haitai Huake 4th Road, Huayuan Industrial Zone, Binhai High Tech Zone, Tianjin 300384, China
Ma S: Electric Power Research Institute, State Grid Tianjin Electric Power Company, No. 8, Haitai Huake 4th Road, Huayuan Industrial Zone, Binhai High Tech Zone, Tianjin 300384, China
Xu N: Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, China
Xiang T: State Grid Tianjin Electric Power Company, No. 39 Wujing, Guangfu Street, Hebei District, Tianjin 300010, China
Han X: Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, China
Mu C: Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin 300072, China
Jin Y: State Grid Tianjin Electric Power Company, No. 39 Wujing, Guangfu Street, Hebei District, Tianjin 300010, China
Journal Name
Energies
Volume
15
Issue
19
First Page
7047
Year
2022
Publication Date
2022-09-25
ISSN
1996-1073
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Original Submission
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PII: en15197047, Publication Type: Journal Article
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LAPSE:2023.9148v1
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