A short-term wind power prediction model based on the improved hippopotamus optimization algorithm and TCN-BiGRU-self-attention

Abstract To address the intermittency and volatility of wind power generation, this paper proposes a hybrid forecasting model for short-term wind power prediction. It integrates a Temporal Convolutional Network (TCN), a Bidirectional Gated Recurrent Unit (BiGRU), a Self-Attention (SA) mechanism, and...

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Dades bibliogràfiques

Autors principals:	Mengling Zhao, Liguo Wang, Jian Huang
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-04-01
Col·lecció:	Scientific Reports
Matèries:	Bidirectional gated recurrent unit Improved hippopotamus optimization algorithm Temporal convolutional network Wind power prediction
Accés en línia:	https://doi.org/10.1038/s41598-026-49575-z
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