Optimal Joint Scheduling and Forecasting of Photovoltaic and Wind Power Generation Based on Transformer-BiLSTM

Addressing the challenge of coordinated dispatch between wind/solar and thermal power in new energy grids, this research proposes a thermal power unit output prediction method based on a Transformer-BiLSTM hybrid deep learning model. First, a simulated annealing algorithm optimizes the output config...

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Detalles Bibliográficos

Autores principales:	Wei Luo, Liyuan Zhu, Defa Cao, Wei Wu, Yi Yang, Jiamin Zhang, Long Wang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2026-03-01
Colección:	Energies
Materias:	photo-thermal power generation wind power generation scheduling prediction transformer BiLSTM
Acceso en línea:	https://www.mdpi.com/1996-1073/19/7/1651
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