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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Detalles Bibliográficos

Principais autores:	Xiaojun Hua, Zhiming Zhang, Tao Ye, Zida Song, Yun Shao, Yixin Su
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2025-09-01
Series:	Energies
Assuntos:	short-term PV power prediction empirical mode decomposition kernel principal component analysis neural network starfish optimization algorithm
Acceso en liña:	https://www.mdpi.com/1996-1073/18/19/5124
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