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Short-term forecasting and uncertainty analysis of wind power based on long short-term memory, cloud model and non-parametric kernel density estimation

Citations

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Cited by:

  1. Huang, Wei & Shao, Changzheng & Hu, Bo & Li, Weizhan & Sun, Yue & Xie, Kaigui & Zio, Enrico & Li, Wenyuan, 2023. "A restoration-clustering-decomposition learning framework for aging-related failure rate estimation of distribution transformers," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
  2. Zheng, Xidong & Bai, Feifei & Zeng, Ziyang & Jin, Tao, 2024. "A new methodology to improve wind power prediction accuracy considering power quality disturbance dimension reduction and elimination," Energy, Elsevier, vol. 287(C).
  3. Zhang, Yagang & Zhao, Yunpeng & Shen, Xiaoyu & Zhang, Jinghui, 2022. "A comprehensive wind speed prediction system based on Monte Carlo and artificial intelligence algorithms," Applied Energy, Elsevier, vol. 305(C).
  4. Ren, Mifeng & Shi, Yujing & Sun, Fang & Zhang, Wenjie & Chen, Junghui, 2026. "Enhanced probabilistic forecasting of wind power using a distribution-free PDF evolution model," Renewable Energy, Elsevier, vol. 258(C).
  5. Sandra Minerva Valdivia-Bautista & José Antonio Domínguez-Navarro & Marco Pérez-Cisneros & Carlos Jesahel Vega-Gómez & Beatriz Castillo-Téllez, 2023. "Artificial Intelligence in Wind Speed Forecasting: A Review," Energies, MDPI, vol. 16(5), pages 1-28, March.
  6. Chen, Yuejiang & Xiao, Jiang-Wen & Wang, Yan-Wu & Luo, Yunfeng, 2025. "Non-crossing quantile probabilistic forecasting of cluster wind power considering spatio-temporal correlation," Applied Energy, Elsevier, vol. 377(PA).
  7. 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).
  8. Abdullah H. Al-Nefaie & Theyazn H. H. Aldhyani, 2023. "Predicting CO 2 Emissions from Traffic Vehicles for Sustainable and Smart Environment Using a Deep Learning Model," Sustainability, MDPI, vol. 15(9), pages 1-21, May.
  9. Liu, Tianhong & Qi, Shengli & Qiao, Xianzhu & Liu, Sixing, 2024. "A hybrid short-term wind power point-interval prediction model based on combination of improved preprocessing methods and entropy weighted GRU quantile regression network," Energy, Elsevier, vol. 288(C).
  10. Wang, Huan & Liao, Shengli & Liu, Benxi & Zhao, Hongye & Ma, Xiangyu & Zhou, Binbin, 2024. "Long-term complementary scheduling model of hydro-wind-solar under extreme drought weather conditions using an improved time-varying hedging rule," Energy, Elsevier, vol. 305(C).
  11. Wang, Xiaodi & Hao, Yan & Yang, Wendong, 2024. "Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy," Energy, Elsevier, vol. 297(C).
  12. Jingtao Huang & Weina Zhang & Jin Qin & Shuzhong Song, 2024. "Ultra-Short-Term Wind Power Prediction Based on eEEMD-LSTM," Energies, MDPI, vol. 17(1), pages 1-18, January.
  13. Fan, Yukun & Liu, Weifeng & Zhu, Feilin & Wang, Sen & Yue, Hao & Zeng, Yurou & Xu, Bin & Zhong, Ping-an, 2024. "Short-term stochastic multi-objective optimization scheduling of wind-solar-hydro hybrid system considering source-load uncertainties," Applied Energy, Elsevier, vol. 372(C).
  14. Yang, Yang & Lang, Jin & Wu, Jian & Zhang, Yanyan & Su, Lijie & Song, Xiangman, 2022. "Wind speed forecasting with correlation network pruning and augmentation: A two-phase deep learning method," Renewable Energy, Elsevier, vol. 198(C), pages 267-282.
  15. Farkas, Hannah & Linsenmeier, Manuel & Talevi, Marta & Avner, Paolo & Jafino, Bramka Arga & Sidibe, Moussa, 2025. "The Economic Value of Weather Forecasts : A Quantitative Systematic Literature Review," Policy Research Working Paper Series 11213, The World Bank.
  16. Guo, Hongxia & Chen, Lingxuan & Wang, Zhaocai & Li, Lin, 2025. "Day-ahead prediction of electric vehicle charging demand based on quadratic decomposition and dual attention mechanisms," Applied Energy, Elsevier, vol. 381(C).
  17. Fan Li & Hongzhen Wang & Dan Wang & Dong Liu & Ke Sun, 2025. "A Review of Wind Power Prediction Methods Based on Multi-Time Scales," Energies, MDPI, vol. 18(7), pages 1-47, March.
  18. Yaofeng Yang & Yajuan Chen & Xiuqing Li, 2024. "Spatial and Temporal Distribution and Influencing Factors of “Water-Energy-Food-Ecology” System Resilience," Land, MDPI, vol. 14(1), pages 1-23, December.
  19. Vladimir Simankov & Pavel Buchatskiy & Semen Teploukhov & Stefan Onishchenko & Anatoliy Kazak & Petr Chetyrbok, 2023. "Review of Estimating and Predicting Models of the Wind Energy Amount," Energies, MDPI, vol. 16(16), pages 1-24, August.
  20. Jha, Amit Prakash & Mahajan, Aarushi & Singh, Sanjay Kumar & Kumar, Piyush, 2022. "Renewable energy proliferation for sustainable development: Role of cross-border electricity trade," Renewable Energy, Elsevier, vol. 201(P1), pages 1189-1199.
  21. Yiyang Sun & Xiangwen Wang & Junjie Yang, 2022. "Modified Particle Swarm Optimization with Attention-Based LSTM for Wind Power Prediction," Energies, MDPI, vol. 15(12), pages 1-17, June.
  22. Dongxiao Niu & Gengqi Wu & Zhengsen Ji & Dongyu Wang & Yuying Li & Tian Gao, 2021. "Evaluation of Provincial Carbon Neutrality Capacity of China Based on Combined Weight and Improved TOPSIS Model," Sustainability, MDPI, vol. 13(5), pages 1-18, March.
  23. Jiang, Sufan & Wu, Chuanshen & Gao, Shan & Pan, Guangsheng & Liu, Yu & Zhao, Xin & Wang, Sicheng, 2022. "Robust frequency risk-constrained unit commitment model for AC-DC system considering wind uncertainty," Renewable Energy, Elsevier, vol. 195(C), pages 395-406.
  24. Zhang, Can & Xiao, Xianyong & Wang, Ying & Hou, Michael Z. & Huang, Shudong & Hu, Wenxi & Hu, Ming & Huang, Rui, 2025. "Fine-grained ultra-short-term wind power forecasting based on Temporal Fusion Transformers integrated with turbine power time series clustering," Energy, Elsevier, vol. 335(C).
  25. Chen, Peng & Han, Dezhi, 2022. "Effective wind speed estimation study of the wind turbine based on deep learning," Energy, Elsevier, vol. 247(C).
  26. Deng, Jiewen & Xiao, Zhao & Zhao, Qiancheng & Zhan, Jun & Tao, Jie & Liu, Minghua & Song, Dongran, 2024. "Wind turbine short-term power forecasting method based on hybrid probabilistic neural network," Energy, Elsevier, vol. 313(C).
  27. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Masahiro Furukakoi & Paras Mandal & Tomonobu Senjyu, 2023. "Integrated Multi-Criteria Planning for Resilient Renewable Energy-Based Microgrid Considering Advanced Demand Response and Uncertainty," Energies, MDPI, vol. 16(19), pages 1-25, September.
  28. Insel, Mert Akin & Ozturk, Busranur & Yucel, Ozgun & Sadikoglu, Hasan, 2025. "Generalizable wind power estimation from historic meteorological data by advanced artificial neural networks," Renewable Energy, Elsevier, vol. 246(C).
  29. Wumaier Tuerxun & Chang Xu & Hongyu Guo & Lei Guo & Namei Zeng & Yansong Gao, 2022. "A Wind Power Forecasting Model Using LSTM Optimized by the Modified Bald Eagle Search Algorithm," Energies, MDPI, vol. 15(6), pages 1-19, March.
  30. Mi, Peiyuan & Zhang, Jili & Gao, Jin & Han, Youhua, 2023. "Study on optimal allocation of solar photovoltaic thermal heat pump integrated energy system for domestic hot water," Renewable Energy, Elsevier, vol. 219(P1).
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