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A new method based on Type-2 fuzzy neural network for accurate wind power forecasting under uncertain data

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  1. Zhang, Le & Zhu, Jizhong & Zhang, Di & Liu, Yun, 2023. "An incremental photovoltaic power prediction method considering concept drift and privacy protection," Applied Energy, Elsevier, vol. 351(C).
  2. Prince Waqas Khan & Yung-Cheol Byun & Sang-Joon Lee & Namje Park, 2020. "Machine Learning Based Hybrid System for Imputation and Efficient Energy Demand Forecasting," Energies, MDPI, vol. 13(11), pages 1-23, May.
  3. Mishra, Dillip Kumar & Ghadi, Mojtaba Jabbari & Azizivahed, Ali & Li, Li & Zhang, Jiangfeng, 2021. "A review on resilience studies in active distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  4. Wang, Cong & Zhang, Hongli & Ma, Ping, 2020. "Wind power forecasting based on singular spectrum analysis and a new hybrid Laguerre neural network," Applied Energy, Elsevier, vol. 259(C).
  5. Zhao, Zhen-Yu & Chen, Yu-Long & Li, Heng, 2019. "What affects the development of renewable energy power generation projects in China: ISM analysis," Renewable Energy, Elsevier, vol. 131(C), pages 506-517.
  6. Wang, Huaizhi & Xue, Wenli & Liu, Yitao & Peng, Jianchun & Jiang, Hui, 2020. "Probabilistic wind power forecasting based on spiking neural network," Energy, Elsevier, vol. 196(C).
  7. Kazim, Muhammad & Pirim, Harun & Yadav, Om Prakash & Le, Chau & Le, Trung, 2025. "Analysis of multilayer energy networks: A comprehensive literature review," Applied Energy, Elsevier, vol. 398(C).
  8. Khan, Taimoor & Choi, Chang, 2025. "Attention enhanced dual stream network with advanced feature selection for power forecasting," Applied Energy, Elsevier, vol. 377(PC).
  9. Elham Alzain & Shaha Al-Otaibi & Theyazn H. H. Aldhyani & Ali Saleh Alshebami & Mohammed Amin Almaiah & Mukti E. Jadhav, 2023. "Revolutionizing Solar Power Production with Artificial Intelligence: A Sustainable Predictive Model," Sustainability, MDPI, vol. 15(10), pages 1-21, May.
  10. Wang, Kejun & Qi, Xiaoxia & Liu, Hongda & Song, Jiakang, 2018. "Deep belief network based k-means cluster approach for short-term wind power forecasting," Energy, Elsevier, vol. 165(PA), pages 840-852.
  11. Sarıman, Güncel & Keçebaş, Ali, 2026. "Global renewable energy forecasting using hybrid ML/DL models: Economic and geospatial insights," Energy Policy, Elsevier, vol. 208(C).
  12. Kim, Deockho & Hur, Jin, 2018. "Short-term probabilistic forecasting of wind energy resources using the enhanced ensemble method," Energy, Elsevier, vol. 157(C), pages 211-226.
  13. Xu, Xiaomin & Niu, Dongxiao & Xiao, Bowen & Guo, Xiaodan & Zhang, Lihui & Wang, Keke, 2020. "Policy analysis for grid parity of wind power generation in China," Energy Policy, Elsevier, vol. 138(C).
  14. Antonella R. Finamore & Vito Calderaro & Vincenzo Galdi & Giuseppe Graber & Lucio Ippolito & Gaspare Conio, 2023. "Improving Wind Power Generation Forecasts: A Hybrid ANN-Clustering-PSO Approach," Energies, MDPI, vol. 16(22), pages 1-14, November.
  15. Amir Mosavi & Mohsen Salimi & Sina Faizollahzadeh Ardabili & Timon Rabczuk & Shahaboddin Shamshirband & Annamaria R. Varkonyi-Koczy, 2019. "State of the Art of Machine Learning Models in Energy Systems, a Systematic Review," Energies, MDPI, vol. 12(7), pages 1-42, April.
  16. Nathan Oaks Farrar & Mohd Hasan Ali & Dipankar Dasgupta, 2023. "Artificial Intelligence and Machine Learning in Grid Connected Wind Turbine Control Systems: A Comprehensive Review," Energies, MDPI, vol. 16(3), pages 1-25, February.
  17. Tahmasebifar, Reza & Moghaddam, Mohsen Parsa & Sheikh-El-Eslami, Mohammad Kazem & Kheirollahi, Reza, 2020. "A new hybrid model for point and probabilistic forecasting of wind power," Energy, Elsevier, vol. 211(C).
  18. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2023. "Predictive operation optimization of multi-energy virtual power plant considering behavior uncertainty of diverse stakeholders," Energy, Elsevier, vol. 280(C).
  19. Khan, Zulfiqar Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2023. "Dual stream network with attention mechanism for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 338(C).
  20. Paweł Piotrowski & Inajara Rutyna & Dariusz Baczyński & Marcin Kopyt, 2022. "Evaluation Metrics for Wind Power Forecasts: A Comprehensive Review and Statistical Analysis of Errors," Energies, MDPI, vol. 15(24), pages 1-38, December.
  21. 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.
  22. Wen, Yan & Pan, Su & Li, Xinxin & Li, Zibo & Wen, Wuzhenghong, 2024. "Improving multi-site photovoltaic forecasting with relevance amplification: DeepFEDformer-based approach," Energy, Elsevier, vol. 299(C).
  23. Xiaohan Huang & Aihua Jiang, 2022. "Wind Power Generation Forecast Based on Multi-Step Informer Network," Energies, MDPI, vol. 15(18), pages 1-17, September.
  24. Elham M. Al-Ali & Yassine Hajji & Yahia Said & Manel Hleili & Amal M. Alanzi & Ali H. Laatar & Mohamed Atri, 2023. "Solar Energy Production Forecasting Based on a Hybrid CNN-LSTM-Transformer Model," Mathematics, MDPI, vol. 11(3), pages 1-19, January.
  25. Siavash Asiaban & Nezmin Kayedpour & Arash E. Samani & Dimitar Bozalakov & Jeroen D. M. De Kooning & Guillaume Crevecoeur & Lieven Vandevelde, 2021. "Wind and Solar Intermittency and the Associated Integration Challenges: A Comprehensive Review Including the Status in the Belgian Power System," Energies, MDPI, vol. 14(9), pages 1-41, May.
  26. Cuadra, L. & Ocampo-Estrella, I. & Alexandre, E. & Salcedo-Sanz, S., 2019. "A study on the impact of easements in the deployment of wind farms near airport facilities," Renewable Energy, Elsevier, vol. 135(C), pages 566-588.
  27. Wei, Danxiang & Wang, Jianzhou & Niu, Xinsong & Li, Zhiwu, 2021. "Wind speed forecasting system based on gated recurrent units and convolutional spiking neural networks," Applied Energy, Elsevier, vol. 292(C).
  28. Wang, Lin & Tao, Rui & Hu, Huanling & Zeng, Yu-Rong, 2021. "Effective wind power prediction using novel deep learning network: Stacked independently recurrent autoencoder," Renewable Energy, Elsevier, vol. 164(C), pages 642-655.
  29. Tsao, Hao-Han & Leu, Yih-Guang & Chou, Li-Fen, 2021. "A center-of-concentrated-based prediction interval for wind power forecasting," Energy, Elsevier, vol. 237(C).
  30. Muhammad Muhitur Rahman & Md Shafiullah & Syed Masiur Rahman & Abu Nasser Khondaker & Abduljamiu Amao & Md. Hasan Zahir, 2020. "Soft Computing Applications in Air Quality Modeling: Past, Present, and Future," Sustainability, MDPI, vol. 12(10), pages 1-33, May.
  31. Zhang, Ruoyang & Wu, Yu & Zhang, Lei & Xu, Chongbin & Wang, ZeYu & Zhang, Yanfeng & Sun, Xiaomin & Zuo, Xin & Wu, Yuhan & Chen, Qian, 2025. "A multiscale network with mixed features and extended regional weather forecasts for predicting short-term photovoltaic power," Energy, Elsevier, vol. 318(C).
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