Short-Term Wind Power Forecast Based on CNN&LSTM-GRU Model Integrated with CEEMD-SE Algorithm

Short-Term Wind Power Forecast Based on CNN&LSTM-GRU Model Integrated with CEEMD-SE Algorithm

In order to further improve the accuracy of short-term wind power forecast, a CNN & LSTM-GRU based short-term wind power prediction model using CEEMD-SE algorithm is proposed. First, the original wind power output series are decomposed into several intrinsic mode function components and one resi...

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Bibliographic Details
Main Authors: Guohua YANG, Xin QI, Rui JIA, Yifeng LIU, Fei MENG, Xin MA, Xiaowen XING
Format: Article
Language:zho
Published: State Grid Energy Research Institute 2024-02-01
Series:Zhongguo dianli
Subjects:
short-term wind power forecasting
complementary ensemble empirical mode decomposition
sample entropy
long short term memory network
gated recurrent unite
Online Access:https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202302098
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https://www.electricpower.com.cn/CN/10.11930/j.issn.1004-9649.202302098

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