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Dual stream network with attention mechanism for photovoltaic power forecasting

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  1. Zhang, Ziqi & Li, Peng & Ji, Haoran & Zhao, Jinli & Xi, Wei & Wu, Jianzhong & Wang, Chengshan, 2024. "Combined central-local voltage control of inverter-based DG in active distribution networks11The short version of the paper was presented at CUE2023. This paper is a substantial extension of the short," Applied Energy, Elsevier, vol. 372(C).
  2. Huang, Songtao & Zhou, Qingguo & Shen, Jun & Zhou, Heng & Yong, Binbin, 2024. "Multistage spatio-temporal attention network based on NODE for short-term PV power forecasting," Energy, Elsevier, vol. 290(C).
  3. Yongning Zhang & Xiaoying Ren & Fei Zhang & Yulei Liu & Jierui Li, 2024. "A Deep Learning-Based Dual-Scale Hybrid Model for Ultra-Short-Term Photovoltaic Power Forecasting," Sustainability, MDPI, vol. 16(17), pages 1-22, August.
  4. Wang, Xinyu & Ma, Wenping, 2024. "A hybrid deep learning model with an optimal strategy based on improved VMD and transformer for short-term photovoltaic power forecasting," Energy, Elsevier, vol. 295(C).
  5. Rizk M Rizk-Allah & Lobna M Abouelmagd & Ashraf Darwish & Vaclav Snasel & Aboul Ella Hassanien, 2024. "Explainable AI and optimized solar power generation forecasting model based on environmental conditions," PLOS ONE, Public Library of Science, vol. 19(10), pages 1-33, October.
  6. Wu, Han & Du, Pei, 2024. "Dual-stream transformer-attention fusion network for short-term carbon price prediction," Energy, Elsevier, vol. 311(C).
  7. Khan, Zulfiqar Ahmad & Khan, Shabbir Ahmad & Hussain, Tanveer & Baik, Sung Wook, 2024. "DSPM: Dual sequence prediction model for efficient energy management in micro-grid," Applied Energy, Elsevier, vol. 356(C).
  8. Ziran Yuan & Pengli Zhang & Bo Ming & Xiaobo Zheng & Lu Tian, 2023. "Joint Forecasting Method of Wind and Solar Outputs Considering Temporal and Spatial Correlation," Sustainability, MDPI, vol. 15(19), pages 1-16, October.
  9. Khan, Taimoor & Choi, Chang, 2025. "Attention enhanced dual stream network with advanced feature selection for power forecasting," Applied Energy, Elsevier, vol. 377(PC).
  10. Gong, Bin & An, Aimin & Shi, Yaoke & Guan, Haijiao & Jia, Wenchao & Yang, Fazhi, 2024. "An interpretable hybrid spatiotemporal fusion method for ultra-short-term photovoltaic power prediction," Energy, Elsevier, vol. 308(C).
  11. Hong Wu & Haipeng Liu & Huaiping Jin & Yanping He, 2024. "Ultra-Short-Term Photovoltaic Power Prediction by NRGA-BiLSTM Considering Seasonality and Periodicity of Data," Energies, MDPI, vol. 17(18), pages 1-19, September.
  12. Yao, Haowei & Qu, Pengyu & Qin, Hengjie & Lou, Zhen & Wei, Xiaoge & Song, Huaitao, 2024. "Multidimensional electric power parameter time series forecasting and anomaly fluctuation analysis based on the AFFC-GLDA-RL method," Energy, Elsevier, vol. 313(C).
  13. Yang, Yanru & Liu, Yu & Zhang, Yihang & Shu, Shaolong & Zheng, Junsheng, 2025. "DEST-GNN: A double-explored spatio-temporal graph neural network for multi-site intra-hour PV power forecasting," Applied Energy, Elsevier, vol. 378(PA).
  14. Pei, Jingyin & Dong, Yunxuan & Guo, Pinghui & Wu, Thomas & Hu, Jianming, 2024. "A Hybrid Dual Stream ProbSparse Self-Attention Network for spatial–temporal photovoltaic power forecasting," Energy, Elsevier, vol. 305(C).
  15. 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).
  16. Habib, Md. Ahasan & Hossain, M.J., 2024. "Advanced feature engineering in microgrid PV forecasting: A fast computing and data-driven hybrid modeling framework," Renewable Energy, Elsevier, vol. 235(C).
  17. Zhu, Jianhua & He, Yaoyao, 2025. "A novel hybrid model based on evolving multi-quantile long and short-term memory neural network for ultra-short-term probabilistic forecasting of photovoltaic power," Applied Energy, Elsevier, vol. 377(PC).
  18. 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).
  19. Meshari D. Alanazi & Ahmad Saeed & Muhammad Islam & Shabana Habib & Hammad I. Sherazi & Sheroz Khan & Mohammad Munawar Shees, 2023. "Enhancing Short-Term Electrical Load Forecasting for Sustainable Energy Management in Low-Carbon Buildings," Sustainability, MDPI, vol. 15(24), pages 1-17, December.
  20. Niu, Yunbo & Wang, Jianzhou & Zhang, Ziyuan & Luo, Tianrui & Liu, Jingjiang, 2024. "De-Trend First, Attend Next: A Mid-Term PV forecasting system with attention mechanism and encoder–decoder structure," Applied Energy, Elsevier, vol. 353(PB).
  21. Xie, Tuo & Yun, Xinyao & Zhang, Gang & Li, Hua & Zhang, Kaoshe & Wang, Ruogu, 2024. "Charging station cluster load prediction: Spatiotemporal multi-graph fusion technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 206(C).
  22. Wu, Han & Liang, Yan & Gao, Xiao-Zhi & Du, Pei, 2024. "Auditory-circuit-motivated deep network with application to short-term electricity price forecasting," Energy, Elsevier, vol. 288(C).
  23. Wu, Han & Gao, Xiao-Zhi & Heng, Jia-Ni, 2024. "Bio-multisensory-inspired gate-attention coordination model for forecasting short-term significant wave height," Energy, Elsevier, vol. 294(C).
  24. Hao, Jianhua & Liu, Fangai & Zhang, Weiwei, 2024. "Multi-scale RWKV with 2-dimensional temporal convolutional network for short-term photovoltaic power forecasting," Energy, Elsevier, vol. 309(C).
  25. Chen, Rujian & Liu, Gang & Cao, Yisheng & Xiao, Gang & Tang, Jianchao, 2024. "CGAformer: Multi-scale feature Transformer with MLP architecture for short-term photovoltaic power forecasting," Energy, Elsevier, vol. 312(C).
  26. Peng, Simin & Zhu, Junchao & Wu, Tiezhou & Yuan, Caichenran & Cang, Junjie & Zhang, Kai & Pecht, Michael, 2024. "Prediction of wind and PV power by fusing the multi-stage feature extraction and a PSO-BiLSTM model," Energy, Elsevier, vol. 298(C).
  27. Fatma Mazen Ali Mazen & Yomna Shaker & Rania Ahmed Abul Seoud, 2023. "Forecasting of Solar Power Using GRU–Temporal Fusion Transformer Model and DILATE Loss Function," Energies, MDPI, vol. 16(24), pages 1-24, December.
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