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2. Online decoupling feature framework for optimal probabilistic load forecasting in concept drift environments. (2025). Cao, Chaojin ; He, Yaoyao ; Yang, Xiaodong.
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3. Wind power forecasting system with data enhancement and algorithm improvement. (2024). Zhang, Yagang ; Kong, Xue ; Cheng, Xiaodan ; Wang, Jingchao.
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4. Characterizing ramp events in floating offshore wind power through a fully coupled electrical-mechanical mathematical model. (2024). Chen, Lingte ; Yang, Jin ; Lou, Chengwei.
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5. Quantile-transformed multi-attention residual framework (QT-MARF) for medium-term PV and wind power prediction. (2024). Shu, Zhaokun ; Ling, Qiang ; Usman, Muhammad ; Mansoor, Majad ; Mirza, Adeel Feroz.
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6. A transferable federated learning approach for wind power prediction based on active privacy clustering and knowledge merge. (2024). Wu, Rong ; Cong, Feiyun ; Lin, Xiaojie ; Zhong, Wei.
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7. A comprehensive framework of the decomposition-based hybrid method for ultra-short-term wind power forecasting with on-site application. (2024). Zhou, Jiaxuan ; Yang, Shixi ; Duan, Jiangman ; Mei, Yiming ; Gu, Xiwen.
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8. 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. (2024). Fang, Guozhong ; Ma, Chenglian ; Huang, Tao ; Guo, Yunfeng ; Yang, Mao.
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9. Very short-term wind power forecasting considering static data: An improved transformer model. (2024). Srinivasan, Dipti ; Chung, C Y ; Zhang, Wenjie ; Sun, Yonghui ; Wang, Sen.
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10. Two-stage correction prediction of wind power based on numerical weather prediction wind speed superposition correction and improved clustering. (2024). Guo, Yunfeng ; Huang, Tao ; Yang, Mao ; Fan, Fulin.
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11. Probabilistic wind power forecasting resilient to missing values: An adaptive quantile regression approach. (2024). Wen, Honglin.
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12. Novel wind power ensemble forecasting system based on mixed-frequency modeling and interpretable base model selection strategy. (2024). Hao, Yan ; Wang, Xiaodi ; Yang, Wendong.
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13. An ultra-short-term wind power prediction method based on spatial-temporal attention graph convolutional model. (2024). Lv, Yunlong ; Wu, Yufan ; Hu, Qin ; Lin, Huiyao ; Xu, Hang.
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14. Fractional-order long-term price guidance mechanism based on bidirectional prediction with attention mechanism for electric vehicle charging. (2024). Cao, YI ; Yin, Linfei ; Hu, Likun.
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15. Wind power forecasting based on manifold learning and a double-layer SWLSTM model. (2024). He, Yan ; Ma, Ping ; Zhang, Hong-Li ; Wang, Cong.
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16. Ultra-short-term wind power forecasting based on personalized robust federated learning with spatial collaboration. (2024). Zhao, Yuan ; Zheng, Yingying ; Pan, Shiji ; Ye, Lin ; Liao, Haohan.
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17. High and low frequency wind power prediction based on Transformer and BiGRU-Attention. (2024). Yang, Wei ; Wang, Shuangxin ; Yin, Qingyan ; Shi, Jiarong.
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18. Auditory-circuit-motivated deep network with application to short-term electricity price forecasting. (2024). Liang, Yan ; Gao, Xiao-Zhi ; Du, Pei ; Wu, Han.
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19. A novel ultra-short-term wind power prediction model jointly driven by multiple algorithm optimization and adaptive selection. (2024). Li, Xuefeng ; Lin, Qingcheng ; Xiao, Hui ; Cai, Huiling ; Liu, Hanwei.
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20. A privacy-preserving framework integrating federated learning and transfer learning for wind power forecasting. (2024). Zhang, Zhen ; Tang, Yugui.
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21. A novel chaotic time series wind power point and interval prediction method based on data denoising strategy and improved coati optimization algorithm. (2024). Wang, Zewei ; Yuan, Yue ; Fu, Xiaoling ; Yang, Ming ; Lin, Hong.
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22. Multi-market P2P trading of cooling–heating-power-hydrogen integrated energy systems: An equilibrium-heuristic online prediction optimization approach. (2024). Bu, Siqi ; Zhang, Rongquan ; Li, Gangqiang.
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23. Analysis of Wind Turbine Equipment Failure and Intelligent Operation and Maintenance Research. (2023). Fan, Yisa ; Li, Songyin ; Shangguan, Linjian ; Peng, Han ; Zhang, Hai.
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24. Electrical load forecasting based on variable T-distribution and dual attention mechanism. (2023). Wang, Yingzhou ; Zhang, Xiuyu.
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