Hybrid model based on similar power extraction and improved temporal convolutional network for probabilistic wind power forecasting-Reference-Cited by-同舟云学术

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Hybrid model based on similar power extraction and improved temporal convolutional network for probabilistic wind power forecasting

Published:2024-09 Issue: Volume:304 Page:131966
ISSN:0360-5442
Container-title:Energy
language:en
Short-container-title:Energy

Author:

Chen Yuejiang,He Yingjing,Xiao Jiang-Wen^ORCID,Wang Yan-Wu^ORCID,Li Yuanzheng

Publisher

Elsevier BV

Reference48 articles.

1. Short-term wind speed interval prediction based on ensemble GRU model;Li;IEEE Trans Sustain Energy,2020

2. An efficient approach to power system uncertainty analysis with high-dimensional dependencies;Wang;IEEE Trans Power Syst,2017

3. A hybrid statistical method to predict wind speed and wind power;Liu;Renew Energy,2010

4. Ensemble methods for wind and solar power forecasting—A state-of-the-art review;Ren;Renew Sustain Energy Rev,2015

5. Retracted: Forecasting model for wind power integrating least squares support vector machine, singular spectrum analysis, deep belief network, and locality-sensitive hashing;Habib;Wind Energy,2020

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Short-Term Wind Power Prediction Based on a Variational Mode Decomposition–BiTCN–Psformer Hybrid Model;Energies;2024-08-17

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