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...

Full description

Saved in:
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
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1996-1073/17/24/6454

Similar Items