Enhancing wind power forecasting accuracy through LSTM with adaptive wind speed calibration (C-LSTM)

Enhancing wind power forecasting accuracy through LSTM with adaptive wind speed calibration (C-LSTM)

Abstract Wind power constitutes a pivotal component in the quest for carbon neutrality, serving as a principal renewable energy source. Enhancing the accuracy of wind power forecasting facilitates more efficient exploitation of this resource, with deep-learning models, notably Long Short-Term Memory...

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Bibliographic Details
Main Authors: Ding Wang, Min Xu, Zhu Guangming, Futao Luo, Jiaxin Gao, Yuntian Chen
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Subjects:
Wind power forecasting
LSTM
Adaptive wind speed calibration
C-LSTM
Online Access:https://doi.org/10.1038/s41598-025-89398-y

Internet

https://doi.org/10.1038/s41598-025-89398-y

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