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Very Short-term Probabilistic Prediction for Regional Wind Power Generation Based on OPNPIs

Yan Zhou Yonghui Sun Sen Wang Rabea Jamil Mahfoud Dongchen Hou Jianxi Wang

CSEE Journal of Power and Energy Systems2026，Vol.12Issue(2)：P.803-812,10.

CSEE Journal of Power and Energy Systems2026，Vol.12Issue(2)：P.803-812,10.DOI:10.17775/CSEEJPES.2022.02790

Very Short-term Probabilistic Prediction for Regional Wind Power Generation Based on OPNPIs

Yan Zhou ¹Yonghui Sun ¹Sen Wang ¹Rabea Jamil Mahfoud ²Dongchen Hou ¹Jianxi Wang¹

作者信息

1. College of Energy and Electrical Engineering,Hohai University,Nanjing 210098,China
2. College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China
折叠

摘要

关键词

Detrending-based/partial/cross-correlation/analysis/Huber-based/approach/nonparametric/prediction/intervals/overall/performance/regional/wind/power/generation

分类

信息技术与安全科学

引用本文复制引用

Yan Zhou,Yonghui Sun,Sen Wang,Rabea Jamil Mahfoud,Dongchen Hou,Jianxi Wang..Very Short-term Probabilistic Prediction for Regional Wind Power Generation Based on OPNPIs[J].CSEE Journal of Power and Energy Systems,2026,12(2):P.803-812,10.

基金项目

supported by the National Natural Science Foundation of China(62073121) （62073121）

National Key R&D Program of China Technology and application of wind power/photovoltaic power prediction for promoting renewable energy consumption(2018YFB0904200) （2018YFB0904200）

eponymous Complement S&T Program of State Grid Corporation of China(SGLNDK0OKJJS1800266)。（SGLNDK0OKJJS1800266）

CSEE Journal of Power and Energy Systems

ISSN：2096-0042

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