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Very Short-Term Forecasting of Distributed PV Power Using GSTANN

Tiechui Yao Jue Wang Yangang Wang Pei Zhang Haizhou Cao Xuebin Chi Min Shi

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(4)：P.1491-1501,11.

CSEE Journal of Power and Energy Systems2024，Vol.10Issue(4)：P.1491-1501,11.DOI:10.17775/CSEEJPES.2022.00110

Very Short-Term Forecasting of Distributed PV Power Using GSTANN

Tiechui Yao ¹Jue Wang ¹Yangang Wang ¹Pei Zhang ²Haizhou Cao ¹Xuebin Chi ¹Min Shi³

作者信息

1. Computer Network Information Center of the Chinese Academy of Sciences,Beijing 100190,China University of Chinese Academy of Sciences,Beijing 100190,China
2. School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China
3. State Grid Hebei Electric Power Co.,Ltd.,Shijiazhuang 050000,China
折叠

摘要

关键词

Distributed photovoltaic power forecasting/graph convolutional networks/satellite images/spatial-temporal attention

分类

信息技术与安全科学

引用本文复制引用

Tiechui Yao,Jue Wang,Yangang Wang,Pei Zhang,Haizhou Cao,Xuebin Chi,Min Shi..Very Short-Term Forecasting of Distributed PV Power Using GSTANN[J].CSEE Journal of Power and Energy Systems,2024,10(4):P.1491-1501,11.

基金项目

supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA27000000)。（No.XDA27000000）

CSEE Journal of Power and Energy Systems

OACSTPCDEI

ISSN：2096-0042

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