Ultra-Short-Term Wind Power Prediction Based on eEEMD-LSTM

Ultra-Short-Term Wind Power Prediction Based on eEEMD-LSTM

The intermittent and random nature of wind brings great challenges to the accurate prediction of wind power; a single model is insufficient to meet the requirements of ultra-short-term wind power prediction. Although ensemble empirical mode decomposition (EEMD) can be used to extract the time series...

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Bibliographic Details
Main Authors: Jingtao Huang, Weina Zhang, Jin Qin, Shuzhong Song
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Energies
Subjects:
wind power prediction
entropy ensemble empirical mode decomposition (eEEMD)
differentiated training
long short-term memory (LSTM)
Online Access:https://www.mdpi.com/1996-1073/17/1/251

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https://www.mdpi.com/1996-1073/17/1/251

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