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Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness

Citations

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Cited by:

  1. Zhang, Chao & Yin, Wanjun & Wen, Tao, 2024. "An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid," Energy, Elsevier, vol. 287(C).
  2. Zhang, Haipeng & Wang, Jianzhou & Qian, Yuansheng & Li, Qiwei, 2024. "Point and interval wind speed forecasting of multivariate time series based on dual-layer LSTM," Energy, Elsevier, vol. 294(C).
  3. Lu, Hongkun & Gao, Xiaoxia & Yu, Jinxiao & Zhao, Qiansheng & Zhu, Xiaoxun & Ma, Wanli & Cao, Jingyuan & Wang, Yu, 2025. "Analysis and prediction of incoming wind speed for turbines in complex wind farm: Accounting for meteorological factors and spatiotemporal characteristics of wind farm," Applied Energy, Elsevier, vol. 381(C).
  4. Li, Shoujun & Miao, Yanzi, 2025. "Wind power forecasting in China based on a novel variable order grey Bernoulli model with weighted time-driven term," Energy, Elsevier, vol. 336(C).
  5. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2025. "LSTM and Transformer-based framework for bias correction of ERA5 hourly wind speeds," Energy, Elsevier, vol. 328(C).
  6. Wei, Jiangxia & Zhang, Weiqiang & Zhang, Wenjie & Ren, Mifeng & Xu, Xinying & Cheng, Lan, 2025. "DBSTN: A dual-branch spatio-temporal network for wind power prediction using multi-modal fusion," Energy, Elsevier, vol. 341(C).
  7. 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).
  8. Yang, Mao & Han, Chao & Zhang, Wei & Wang, Bo, 2024. "A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information," Energy, Elsevier, vol. 294(C).
  9. Meng, Anbo & Chen, Shu & Ou, Zuhong & Xiao, Jianhua & Zhang, Jianfeng & Chen, Shun & Zhang, Zheng & Liang, Ruduo & Zhang, Zhan & Xian, Zikang & Wang, Chenen & Yin, Hao & Yan, Baiping, 2022. "A novel few-shot learning approach for wind power prediction applying secondary evolutionary generative adversarial network," Energy, Elsevier, vol. 261(PA).
  10. Zhao, Jing & Guo, Yiyi & Lin, Yihua & Zhao, Zhiyuan & Guo, Zhenhai, 2024. "A novel dynamic ensemble of numerical weather prediction for multi-step wind speed forecasting with deep reinforcement learning and error sequence modeling," Energy, Elsevier, vol. 302(C).
  11. Li, Chenghan & Guo, Ye & Xu, Yinliang, 2025. "A double deep reinforcement learning-based adaptive framework for decision-optimal wind power interval prediction," Energy, Elsevier, vol. 329(C).
  12. Cui, Xiwen & Yu, Xiaoyu & Niu, Dongxiao, 2024. "The ultra-short-term wind power point-interval forecasting model based on improved variational mode decomposition and bidirectional gated recurrent unit improved by improved sparrow search algorithm and attention mechanism," Energy, Elsevier, vol. 288(C).
  13. Chen, Fuhao & Yan, Jie & Liu, Yongqian & Yan, Yamin & Tjernberg, Lina Bertling, 2024. "A novel meta-learning approach for few-shot short-term wind power forecasting," Applied Energy, Elsevier, vol. 362(C).
  14. Jiawei Zhang & Rongquan Zhang & Yanfeng Zhao & Jing Qiu & Siqi Bu & Yuxiang Zhu & Gangqiang Li, 2023. "Deterministic and Probabilistic Prediction of Wind Power Based on a Hybrid Intelligent Model," Energies, MDPI, vol. 16(10), pages 1-15, May.
  15. 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).
  16. Liang, Xuefeng & Hu, Zetian & Zhang, Jun & Chen, Han & Gu, Qingshui & You, Xiaochuan, 2025. "Developing a robust wind power forecasting method: Integrating data repair, feature screening, and economic impact analysis for practical applications," Renewable Energy, Elsevier, vol. 247(C).
  17. Hu, Yue & Liu, Hanjing & Wu, Senzhen & Zhao, Yuan & Wang, Zhijin & Liu, Xiufeng, 2024. "Temporal collaborative attention for wind power forecasting," Applied Energy, Elsevier, vol. 357(C).
  18. Dong, Fuxiang & Ju, Shiyu & Liu, Jinfu & Yu, Daren & Li, Hong, 2025. "An ultra-short-term wind power robust prediction method considering the periodic impact of wind direction," Renewable Energy, Elsevier, vol. 247(C).
  19. Lu, Hongkun & Gao, Xiaoxia & Xu, Zongyuan & Xiao, Huan & Gao, Yihan & Zhang, Huanqiang & Ma, Hongyu & Zhu, Yuting & Zhu, Xiaoxun & Wang, Yu, 2025. "Wind direction prediction combined with wind speed in a wind farm," Energy, Elsevier, vol. 333(C).
  20. Liu, Pihui & Li, Mengdi & Han, Chuanfeng & Meng, Lingpeng & Shao, Zhiguo, 2025. "From input to output: Unraveling the Spatio - temporal pattern and driving factors of the coupling coordination between wind power efficiency and installed capacity in China," Applied Energy, Elsevier, vol. 396(C).
  21. Yang, Mao & Guo, Yunfeng & Huang, Yutong, 2023. "Wind power ultra-short-term prediction method based on NWP wind speed correction and double clustering division of transitional weather process," Energy, Elsevier, vol. 282(C).
  22. Lele Wang & Dongqing Zhang, 2025. "Enhancing Wind Power Forecasting Accuracy Based on OPESC-Optimized CNN-BiLSTM-SA Model," Mathematics, MDPI, vol. 13(13), pages 1-24, July.
  23. Qiu, Lihong & Ma, Wentao & Feng, Xiaoyang & Dai, Jiahui & Dong, Yuzhuo & Duan, Jiandong & Chen, Badong, 2024. "A hybrid PV cluster power prediction model using BLS with GMCC and error correction via RVM considering an improved statistical upscaling technique," Applied Energy, Elsevier, vol. 359(C).
  24. Ge, Chang & Yan, Jie & Zhang, Haoran & Li, Yuhao & Wang, Han & Liu, Yongqian, 2024. "Joint short-term power forecasting of hydro-wind-photovoltaic considering spatiotemporal delay of weather processes," Renewable Energy, Elsevier, vol. 237(PB).
  25. Chen, Yunxiao & Lin, Chaojing & Zhang, Yilan & Liu, Jinfu & Yu, Daren, 2024. "Proactive failure warning for wind power forecast models based on volatility indicators analysis," Energy, Elsevier, vol. 305(C).
  26. Ye, Lin & Li, Yilin & Pei, Ming & Zhao, Yongning & Li, Zhuo & Lu, Peng, 2022. "A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching," Applied Energy, Elsevier, vol. 327(C).
  27. Wei, Xingchen & Wu, Xinyu & Yoshimura, Kei & Cheng, Chuntian & Huang, Hao & Ding, Zhendong & Song, Yuhang, 2025. "Climate-informed long-term forecasting of wind and photovoltaic power using a hybrid DWT–BES–CNN–LSTM model," Energy, Elsevier, vol. 338(C).
  28. Liu, Huizhou & Huang, Juntao & Hu, Jinqiu & Zhang, Junfeng & Huang, Mengxing, 2025. "Enhancing wind power prediction accuracy: A novel method integrating seasonal temporal factors and advanced spatio-temporal feature extraction," Energy, Elsevier, vol. 336(C).
  29. Agnieszka Dudziak & Arkadiusz Małek & Andrzej Marciniak & Jacek Caban & Jarosław Seńko, 2024. "Probabilistic Analysis of Green Hydrogen Production from a Mix of Solar and Wind Energy," Energies, MDPI, vol. 17(17), pages 1-22, September.
  30. Xuehui Wang & Yongsheng Wang & Yongsheng Qi & Jiajing Gao & Fan Yang & Jiaxuan Lu, 2025. "An Ultra-Short-Term Wind Power Prediction Method Based on the Fusion of Multiple Technical Indicators and the XGBoost Algorithm," Energies, MDPI, vol. 18(12), pages 1-21, June.
  31. Zhang, Yagang & Zhang, Jinghui & Yu, Leyi & Pan, Zhiya & Feng, Changyou & Sun, Yiqian & Wang, Fei, 2022. "A short-term wind energy hybrid optimal prediction system with denoising and novel error correction technique," Energy, Elsevier, vol. 254(PC).
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