Wind power probabilistic forecasting based on combined decomposition and deep learning quantile regression

Wind power probabilistic forecasting based on combined decomposition and deep learning quantile regression

With the expansion of scale of the grid-connected wind power, wind power forecasting plays an increasing important role in ensuring the security and steady operation and instructing the dispatch of power systems. In consideration of the randomness and intermittency of wind power, the probabilistic f...

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Bibliographic Details
Main Authors:	Zhenglin Zhu, Yusen Xu, Junzhao Wu, Yiwen Liu, Jianwei Guo, Haixiang Zang
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2022-08-01
Series:	Frontiers in Energy Research
Subjects:	probabilistic forecasting combination decomposition quantile regression convolutional neural network bidirectional gated neural network
Online Access:	https://www.frontiersin.org/articles/10.3389/fenrg.2022.937240/full

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