Short-term multi-step wind power prediction model based on Pt-Transformer neural network integrating spatio-temporal feature and sparse attention

•A wind power forecasting method based on the time series Transformer model is proposed.•Novel model improves noisy data handling, time-series dependency capture, and efficiency.•Introduce a multi-step autoregressive prediction framework using Teacher forcing. The accuracy and stability of wind powe...

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Veröffentlicht in:	Electric power systems research Jg. 248; S. 111970
Hauptverfasser:	Zhang, Zhiyan, Sun, Zhenyang, Guo, Xianghui, Guo, Ruipeng, Yang, Xiaoliang, Yang, Pengju
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.11.2025
Schlagworte:	Seasonal trend decomposition Sparse attention mechanism Temporal autoencoder Transformer Wind power prediction Seasonal trend decomposition Sparse attention mechanism Wind power prediction Transformer Temporal autoencoder
ISSN:	0378-7796
Online-Zugang:	Volltext
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