A context-driven dynamic modeling method for ultra-short-term wind power forecastingOA
A context-driven dynamic modeling method for ultra-short-term wind power forecasting
Xuanru Chen;Han Wang;Yuhao Li;Jie Yan;Shuang Han;Yongqian Liu
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.ChinaState Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(NCEPU),Beijing 102206,P.R.China||School of New Energy,North China Electric Power University,Beijing 102206,P.R.China
Ultra-short-term wind power forecastingContext-drivenConcept drift detectionOnline modeling
Ultra-short-term wind power forecastingContext-drivenConcept drift detectionOnline modeling
《全球能源互联网（英文）》 2026 (2)
243-254,12
This work was supported by National Key R&D Pro-gram of China(2025YFE0110900),Inner Mongolia autonomous region"Selecting The Best Candidates to Undertake Key Research"project(2024JBGS0054).
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