Enhanced Short-Term Photovoltaic Power Prediction Through Multi-Method Data Processing and SFOA-Optimized CNN-BiLSTM

The increasing global demand for renewable energy poses significant challenges to grid stability due to the fluctuation and unpredictability of photovoltaic (PV) power generation. To enhance the accuracy of short-term PV power prediction, this study proposes an innovative integrated model that combi...

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書誌詳細

主要な著者:	Xiaojun Hua, Zhiming Zhang, Tao Ye, Zida Song, Yun Shao, Yixin Su
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2025-09-01
シリーズ:	Energies
主題:	short-term PV power prediction empirical mode decomposition kernel principal component analysis neural network starfish optimization algorithm
オンライン･アクセス:	https://www.mdpi.com/1996-1073/18/19/5124
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