Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power

Abstract Accurate and reliable forecasting of wind power is essential for the stable integration of wind energy into the electrical grid. However, the chaotic nature of wind power presents a significant challenge in utilizing data for effective short‐term forecasting, such as 60‐min predictions. Thi...

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Bibliographic Details
Main Authors: Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:IET Renewable Power Generation
Subjects:
Online Access:https://doi.org/10.1049/rpg2.13159
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