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...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Xiaojun Hua, Zhiming Zhang, Tao Ye, Zida Song, Yun Shao, Yixin Su
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2025-09-01
Sarja:	Energies
Aiheet:	short-term PV power prediction empirical mode decomposition kernel principal component analysis neural network starfish optimization algorithm
Linkit:	https://www.mdpi.com/1996-1073/18/19/5124
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