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Optimal Frequency Regulation Based on Characterizing the Air Conditioning Cluster by Online Deep Learning

Yeyan Xu Liangzhong Yao Siyang Liao Yaping Li Jian Xu Fan Cheng

中国电机工程学会电力与能源系统学报（英文版）2022，Vol.8Issue(5)：1373-1387,15.

中国电机工程学会电力与能源系统学报（英文版）2022，Vol.8Issue(5)：1373-1387,15.DOI:10.17775/CSEEJPES.2020.05940

Optimal Frequency Regulation Based on Characterizing the Air Conditioning Cluster by Online Deep Learning

Yeyan Xu ¹Liangzhong Yao ¹Siyang Liao ¹Yaping Li ²Jian Xu ¹Fan Cheng³

作者信息

1. School of Electrical Engineering and Automation,Wuhan University,Wuhan 430072,China
2. China Electric Power Research Institute,Nanjing 210008,China
3. China Electric Power Research Institute,Beijing 100085,China
折叠

摘要

关键词

Air conditioning/demand response chara-cteristic/online deep learning/optimal frequency regulation/sliding mode control

Key words

Air conditioning/demand response chara-cteristic/online deep learning/optimal frequency regulation/sliding mode control

引用本文复制引用

Yeyan Xu,Liangzhong Yao,Siyang Liao,Yaping Li,Jian Xu,Fan Cheng..Optimal Frequency Regulation Based on Characterizing the Air Conditioning Cluster by Online Deep Learning[J].中国电机工程学会电力与能源系统学报（英文版）,2022,8(5):1373-1387,15.

基金项目

This work was supported by State Grid Corporation of China Project Research on Coordinated Technology for Dynamic Demand Response in Frequency Control. （）

中国电机工程学会电力与能源系统学报（英文版）

OACSCDCSTPCDEISCI

ISSN：2096-0042

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