- Chaoshun Li, Geng Tang, Xiaoming Xue, Xinbiao Chen, Ruoheng Wang, Chu Zhang, “The short-term interval prediction of wind power using the deep learning model with gradient descend optimization”, Renewable Energy, 155, 2020, 197
- António Couto, Paula Costa, Teresa Simões, “Identification of Extreme Wind Events Using a Weather Type Classification”, Energies, 14, no. 13, 2021, 3944
- Santiago Díaz, José A. Carta, Alberto Castañeda, “Influence of the variation of meteorological and operational parameters on estimation of the power output of a wind farm with active power control”, Renewable Energy, 159, 2020, 812
- Yongfeng Liu, Fang Liu, Yucong Huang Haotian Li Zhen Fan, 2022 34th Chinese Control and Decision Conference (CCDC), 2022, 165
- Denis Sidorov, Fang Liu, Yonghui Sun, “Machine Learning for Energy Systems”, Energies, 13, no. 18, 2020, 4708
- Lian Lian, Kan He, “Ultra-short-term wind speed prediction based on variational mode decomposition and optimized extreme learning machine”, Wind Engineering, 46, no. 2, 2022, 556
- Yang Yang, Jin Lang, Jian Wu, Yanyan Zhang, Lijie Su, Xiangman Song, “Wind speed forecasting with correlation network pruning and augmentation: A two-phase deep learning method”, Renewable Energy, 198, 2022, 267
- Yuri Bulatov, Andrey Kryukov, Andrey Batuhtin, Konstantin Suslov, Ksenia Korotkova, Denis Sidorov, “Digital Twin Formation Method for Distributed Generation Plants of Cyber–Physical Power Supply Systems”, Mathematics, 10, no. 16, 2022, 2886
- Weicheng Hu, Qingshan Yang, Hua-Peng Chen, Ziting Yuan, Chen Li, Shuai Shao, Jian Zhang, “New hybrid approach for short-term wind speed predictions based on preprocessing algorithm and optimization theory”, Renewable Energy, 179, 2021, 2174
- Paweł Piotrowski, Mirosław Parol, Piotr Kapler, Bartosz Fetliński, “Advanced Forecasting Methods of 5-Minute Power Generation in a PV System for Microgrid Operation Control”, Energies, 15, no. 7, 2022, 2645