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Multi-agent Deep Reinforcement Learning Approach for Temporally Coordinated Demand Response in Microgrids

Chunchao Hu Zexiang Cai Yanxu Zhang

中国电机工程学会电力与能源系统学报（英文版）2025，Vol.11Issue(4)：1512-1522,11.

中国电机工程学会电力与能源系统学报（英文版）2025，Vol.11Issue(4)：1512-1522,11.DOI:10.17775/CSEEJPES.2021.05090

Multi-agent Deep Reinforcement Learning Approach for Temporally Coordinated Demand Response in Microgrids

Chunchao Hu ¹Zexiang Cai ²Yanxu Zhang³

作者信息

1. School of Electrical and Electronic Engineering,South China University of Technology,Guangzhou 510640,China||Zhang China Southern Power Grid Electrical Technology Co.,LTD.
2. School of Electrical and Electronic Engineering,South China University of Technology,Guangzhou 510640,China
3. Zhang China Southern Power Grid Electrical Technology Co.,LTD.
折叠

摘要

关键词

Day-ahead price-based demand response/demand response/hourly direct load control/microgrid/multi-agent deep reinforcement learning

Key words

Day-ahead price-based demand response/demand response/hourly direct load control/microgrid/multi-agent deep reinforcement learning

引用本文复制引用

Chunchao Hu,Zexiang Cai,Yanxu Zhang..Multi-agent Deep Reinforcement Learning Approach for Temporally Coordinated Demand Response in Microgrids[J].中国电机工程学会电力与能源系统学报（英文版）,2025,11(4):1512-1522,11.

基金项目

The work was supported in part by the Guangdong Provincial Key R&D Program under Grant no.2019B111109002. （）

中国电机工程学会电力与能源系统学报（英文版）

ISSN：2096-0042

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