Demand Response Package Model of Electric Vehicle Charging Station Based on LSTM Neural Network and Optimal Operation of Distribution Network

Mingfeng XUE; Xiaobo MAO; Yongtao PAN; Yanhong YANG; Zhenxing ZHAO; Yanjun LI

doi:10.12204/j.issn.1000-7229.2021.06.008

XUE Mingfeng, MAO Xiaobo, PAN Yongtao, YANG Yanhong, ZHAO Zhenxing, LI Yanjun

Electric Power Construction ›› 2021, Vol. 42 ›› Issue (6) : 76-85.

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Electric Power Construction ›› 2021, Vol. 42 ›› Issue (6) : 76-85. DOI: 10.12204/j.issn.1000-7229.2021.06.008

Key Technologies of Electric Vehicle Participating in Power Grid Dispatching?Hosed by Associate Professor FU Zhixin?

Demand Response Package Model of Electric Vehicle Charging Station Based on LSTM Neural Network and Optimal Operation of Distribution Network

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{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2021, 42(6): 76-85 https://doi.org/10.12204/j.issn.1000-7229.2021.06.008

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Administrator：State Grid Corporation of China
Sponsors：
State Grid Economic and Technological Research Institute Co. Ltd
China Power Engineering Consulting Group Co., Ltd
China Electric Power Research Institute
Editor in Chief: GUO Mingqun
Associate Editor-in-Chief:KANG Chongqing, BI Tianshu, LI Hui
Executive Editor-in-Chief:YANG Weihong, SHENG Yi
Editorial Director:WEI Xihui
CN: 11-2583/TM
ISSN: 1000-7229

Address: Tower A225, SGCC, Future Science & Technology Park, Beijing 102209, China
Post Code: 102209
Editor’s Tel: 86-10-66602697
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E-mail：dljs@263.net
Web Site: http://www.cepc.com.cn
Post Issue Number: 82-679
CODEN: DJIIAQ

Received	Published
2020-11-27	2021-06-01
Issue Date
2021-05-28

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