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Deep Reinforcement Learning Based Bi-layer Optimal Scheduling for Microgrids Considering Flexible Load Control

Zitong Zhang Jing Shi Wangwang Yang Zhaofang Song Zexu Chen Dengquan Lin

中国电机工程学会电力与能源系统学报(英文)2023，Vol.9Issue(3)：P.949-962,14.

中国电机工程学会电力与能源系统学报(英文)2023，Vol.9Issue(3)：P.949-962,14.DOI:10.17775/CSEEJPES.2021.06120

Deep Reinforcement Learning Based Bi-layer Optimal Scheduling for Microgrids Considering Flexible Load Control

Zitong Zhang ¹Jing Shi ¹Wangwang Yang ¹Zhaofang Song ¹Zexu Chen ¹Dengquan Lin¹

作者信息

1. the State Key Laboratory of Advanced Electromagnetic Engineering and Technology,School of Electronic Engineering,Huazhong University of Science and Technology,Wuhan 430074,China
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摘要

关键词

Bi-layer optimal scheduling/demand response/deep reinforcement learning/microgrid scheduling

分类

信息技术与安全科学

引用本文复制引用

Zitong Zhang,Jing Shi,Wangwang Yang,Zhaofang Song,Zexu Chen,Dengquan Lin..Deep Reinforcement Learning Based Bi-layer Optimal Scheduling for Microgrids Considering Flexible Load Control[J].中国电机工程学会电力与能源系统学报(英文),2023,9(3):P.949-962,14.

基金项目

supported in part by National Key R&D Program of China under Grant 2021YFB3800200. （）

中国电机工程学会电力与能源系统学报(英文)

OACSCDCSTPCDEI

ISSN：2096-0042

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