A Deep Learning Framework for Day Ahead Wind Power Short-Term Prediction

A Deep Learning Framework for Day Ahead Wind Power Short-Term Prediction

Due to the increasing proportion of wind power connected to the grid, day-ahead wind power prediction plays a more and more important role in the operation of the power system. This paper proposes a day-ahead wind power short-term prediction model based on deep learning (DWT_AE_BiLSTM). Firstly, dis...

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Bibliographic Details
Main Authors: Peihua Xu, Maoyuan Zhang, Zhenhong Chen, Biqiang Wang, Chi Cheng, Renfeng Liu
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Applied Sciences
Subjects:
discrete wavelet transform
autoencoder
bidirectional LSTM
wind power forecasting
Online Access:https://www.mdpi.com/2076-3417/13/6/4042

Internet

https://www.mdpi.com/2076-3417/13/6/4042

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