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Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method

Citations

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Cited by:

  1. Gomez, William & Wang, Fu-Kwun & Sheu, Shey-Huei, 2025. "Short-term smart grid energy forecasting using a hybrid deep learning method on univariate and multivariate data sets," Energy, Elsevier, vol. 335(C).
  2. Jie Du & Shuaizhi Chen & Linlin Pan & Yubao Liu, 2025. "A Wind Speed Prediction Method Based on Signal Decomposition Technology Deep Learning Model," Energies, MDPI, vol. 18(5), pages 1-26, February.
  3. Zhao, Dan & He, Hongying & Luo, Diansheng & Huang, Shoudao & Zhang, Zihan, 2025. "Ultra-short-term wind power forecast based on multi-feature information fusion of GAT-Crossformer," Energy, Elsevier, vol. 340(C).
  4. Cao, Yuzhe & Huang, Xuefei & Liu, Jing & Cai, Defu & Ding, Yuemin & Lu, Renzhi, 2025. "DDRGS2S: A novel spatiotemporal correlation-based deep learning model for wind power prediction," Energy, Elsevier, vol. 338(C).
  5. Qiu, Hong & Shi, Kaikai & Wang, Renfang & Zhang, Liang & Liu, Xiufeng & Cheng, Xu, 2024. "A novel temporal–spatial graph neural network for wind power forecasting considering blockage effects," Renewable Energy, Elsevier, vol. 227(C).
  6. Yang, Ting & Yang, Zhenning & Li, Fei & Wang, Hengyu, 2024. "A short-term wind power forecasting method based on multivariate signal decomposition and variable selection," Applied Energy, Elsevier, vol. 360(C).
  7. Jiang, Meiqin & Che, Jinxing & Li, Shuying & Hu, Kun & Xu, Yifan, 2025. "Incorporating key features from structured and unstructured data for enhanced carbon trading price forecasting with interpretability analysis," Applied Energy, Elsevier, vol. 382(C).
  8. Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
  9. Wang, Jia & Cao, Yuan & Xiong, Xiong, 2025. "Multiscale dependence and risk contagion between European carbon market, energy, and financial markets," Energy, Elsevier, vol. 335(C).
  10. Sun, Xiaoying & Liu, Haizhong, 2024. "Multivariate short-term wind speed prediction based on PSO-VMD-SE-ICEEMDAN two-stage decomposition and Att-S2S," Energy, Elsevier, vol. 305(C).
  11. Yin, Hao & Li, Chen & Chen, Shuxuan & Meng, Anbo, 2025. "Few-shot wind power prediction using sample transfer and imbalanced evolved neural network," Energy, Elsevier, vol. 328(C).
  12. Zhao, Yongning & Zhao, Yuan & Liao, Haohan & Pan, Shiji & Zheng, Yingying, 2025. "Interpreting LASSO regression model by feature space matching analysis for spatio-temporal correlation based wind power forecasting," Applied Energy, Elsevier, vol. 380(C).
  13. Li, Jianfang & Jia, Li & Zhou, Chengyu, 2024. "Probability density function based adaptive ensemble learning with global convergence for wind power prediction," Energy, Elsevier, vol. 312(C).
  14. Jia, Wenchao & An, Aimin & Gong, Bin & Shi, Yaoke & Yan, Zheming, 2026. "A multi-variable driven dual-stage modal-decoupling framework integrating deterministic–uncertainty modeling for wind power forecasting with feature interpretability analysis," Energy, Elsevier, vol. 344(C).
  15. Qin, Rui & Chai, Hwa Kian & Liu, Kai & Yu, Hang & Huang, Jing, 2025. "A hierarchical multi-stage fusion deep learning framework for short-term wind power prediction," Renewable Energy, Elsevier, vol. 253(C).
  16. Bashir, Tasarruf & Wang, Huifang & Tahir, Mustafa & Zhang, Yixiang, 2025. "Wind and solar power forecasting based on hybrid CNN-ABiLSTM, CNN-transformer-MLP models," Renewable Energy, Elsevier, vol. 239(C).
  17. Yang, Mao & Guo, Yunfeng & Huang, Tao & Fan, Fulin & Ma, Chenglian & Fang, Guozhong, 2024. "Wind farm cluster power prediction based on graph deviation attention network with learnable graph structure and dynamic error correction during load peak and valley periods," Energy, Elsevier, vol. 312(C).
  18. Wang, Jianguo & Yuan, Weiru & Zhang, Shude & Cheng, Shun & Han, Lincheng, 2024. "Implementing ultra-short-term wind power forecasting without information leakage through cascade decomposition and attention mechanism," Energy, Elsevier, vol. 312(C).
  19. Ziyu Li & Xianqi Zhang, 2024. "A Novel Coupled Model for Monthly Rainfall Prediction Based on ESMD-EWT-SVD-LSTM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(9), pages 3297-3312, July.
  20. Guo, Lili & Cheng, Quanfeixue & He, Xiangyi & Su, Mengying & Li, Houjian, 2025. "Bioenergy market predictions using AI: Integrating climate change and green finance," Renewable Energy, Elsevier, vol. 250(C).
  21. Liu, Yuqi & Yuan, Weimin & Chen, Weilong & Li, Wenming & Yang, Han & Zhang, Yanru, 2025. "CPLLM-WPF: A multi-scale prompting framework for generalizable wind power forecasting with LLMs," Applied Energy, Elsevier, vol. 402(PA).
  22. Huawei, Mei & Qingyuan, Zhu & Wangbin, Cao, 2025. "A TSFLinear model for wind power prediction with feature decomposition-clustering," Renewable Energy, Elsevier, vol. 248(C).
  23. Zhou, Daixuan & Liu, Yujin & Wang, Xu & Wang, Fuxing & Jia, Yan, 2025. "Combined ultra-short-term photovoltaic power prediction based on CEEMDAN decomposition and RIME optimized AM-TCN-BiLSTM," Energy, Elsevier, vol. 318(C).
  24. Udenze, Peter I. & Gong, Jiaqi & Soltani, Shohreh & Li, Dawen, 2025. "A deep neural network with two-step decomposition technique for predicting ultra-short-term solar power and electrical load," Applied Energy, Elsevier, vol. 382(C).
  25. Huang, Jing & Qin, Rui, 2024. "Elman neural network considering dynamic time delay estimation for short-term forecasting of offshore wind power," Applied Energy, Elsevier, vol. 358(C).
  26. Yao, Xianshuang & Guo, Kangshuai & Lei, Jianqi & Li, Xuanyu, 2024. "Fully connected multi-reservoir echo state networks for wind power prediction," Energy, Elsevier, vol. 312(C).
  27. Geng, Donghan & Zhang, Yongkang & Zhang, Yunlong & Qu, Xingchuang & Li, Longfei, 2025. "A hybrid model based on CapSA-VMD-ResNet-GRU-attention mechanism for ultra-short-term and short-term wind speed prediction," Renewable Energy, Elsevier, vol. 240(C).
  28. Fu, Wenlong & Shao, Mengxin & Zhu, Xinfeng & Zheng, Bo & Liao, Xiang & Mei, Qicheng & Li, Shuai & Xiong, Haowei, 2025. "Dual-path ultra-short-term wind power forecasting based on numerical weather prediction and multi-order temporal dynamic gating fusion," Energy, Elsevier, vol. 335(C).
  29. Xinyu Zhang & Xinyan Qin & Jin Lei & Zhiyuan Zhai & Jianglong Zhang & Zhi Wang, 2024. "A Novel Method on Recognizing Drum Load of Elastic Tooth Drum Pepper Harvester Based on CEEMDAN-KPCA-SVM," Agriculture, MDPI, vol. 14(7), pages 1-20, July.
  30. Jianjing Mao & Jian Zhao & Hongtao Zhang & Bo Gu, 2025. "A Novel Hybrid Deep Learning Model for Day-Ahead Wind Power Interval Forecasting," Sustainability, MDPI, vol. 17(7), pages 1-26, April.
  31. Chudong Shan & Shuai Liu & Shuangjian Peng & Zhihong Huang & Yuanjun Zuo & Wenjing Zhang & Jian Xiao, 2025. "A Wind Power Forecasting Method Based on Lightweight Representation Learning and Multivariate Feature Mixing," Energies, MDPI, vol. 18(11), pages 1-17, June.
  32. Cheng, Runkun & Yang, Di & Liu, Da & Zhang, Guowei, 2024. "A reconstruction-based secondary decomposition-ensemble framework for wind power forecasting," Energy, Elsevier, vol. 308(C).
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