An Advanced BiLSTM Prediction Model for Short-Term Wind-Storage Power Prediction

For enhancing the level of refinement of short-horizon wind-storage power prediction, this paper introduces an advanced BiLSTM prediction model integrating data preprocessing based on the density-based clustering technique known as DBSCAN, partial least squares regression (PLSR), and particle swarm...

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Detalles Bibliográficos

Autores principales:	Muyao Lv, Zejia Liu, Guoqing Wang, Chao Zhang, Yanling Liu, Chao Luo, Jiawei Yu, Yihua Zhu
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2026-05-01
Colección:	Energies
Materias:	wind-storage power prediction BiLSTM DBSCAN PLSR
Acceso en línea:	https://www.mdpi.com/1996-1073/19/11/2666
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