Reactive Power Optimization Method of Power Network Based on Deep Reinforcement Learning Considering Topology Characteristics

Reactive Power Optimization Method of Power Network Based on Deep Reinforcement Learning Considering Topology Characteristics

Aiming at the load fluctuation problem caused by a high proportion of new energy grid connections, a reactive power optimization method based on deep reinforcement learning (DRL) considering topological characteristics is proposed. The proposed method transforms the reactive power optimization probl...

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Bibliographic Details
Main Authors:	Tianhua Chen, Zemei Dai, Xin Shan, Zhenghong Li, Chengming Hu, Yang Xue, Ke Xu
Format:	Article
Language:	English
Published:	MDPI AG 2024-12-01
Series:	Energies
Subjects:	deep reinforcement learning graph convolution topological characteristics reactive power optimization deep Q-network
Online Access:	https://www.mdpi.com/1996-1073/17/24/6454
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