DTCMMA: Efficient Wind-Power Forecasting Based on Dimensional Transformation Combined with Multidimensional and Multiscale Convolutional Attention Mechanism

DTCMMA: Efficient Wind-Power Forecasting Based on Dimensional Transformation Combined with Multidimensional and Multiscale Convolutional Attention Mechanism

With the growing global demand for clean energy, the accuracy of wind-power forecasting plays a vital role in ensuring the stable operation of power systems. However, wind-power generation is significantly influenced by meteorological conditions and is characterized by high uncertainty and multiscal...

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Bibliographic Details
Main Authors: Wenhan Song, Enguang Zuo, Junyu Zhu, Chen Chen, Cheng Chen, Ziwei Yan, Xiaoyi Lv
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Sensors
Subjects:
wind-power forecasting
dimensional transformation
convolutional attention mechanism
deep learning
Online Access:https://www.mdpi.com/1424-8220/25/15/4530
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