The future of forecasting for renewable energy

Citations

Cited by:

1. Zhong, Xiaohui & Chen, Lei & Li, Hao & Fan, Xu & Qian, Wenxu & Liu, Jun & Luo, Enwang & Wu, Libo, 2026. "Improving renewable energy forecasting with FuXi-Energy," Applied Energy, Elsevier, vol. 412(C).
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3. Zhang, Gang & Yang, Dazhi & Galanis, George & Androulakis, Emmanouil, 2022. "Solar forecasting with hourly updated numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
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5. Mayer, Martin János & Yang, Dazhi, 2024. "Optimal place to apply post-processing in the deterministic photovoltaic power forecasting workflow," Applied Energy, Elsevier, vol. 371(C).
6. Marco Raugi & Valentina Consolo & Roberto Rugani, 2024. "The Effect of Increasing Aggregation Levels of Electrical Consumption Data on Renewable Energy Community (REC) Analyses," Energies, MDPI, vol. 17(18), pages 1-25, September.
7. Houndekindo, Freddy & Ouarda, Taha B.M.J., 2025. "LSTM and Transformer-based framework for bias correction of ERA5 hourly wind speeds," Energy, Elsevier, vol. 328(C).
8. Jin, Huaiping & Zhang, Kehao & Fan, Shouyuan & Jin, Huaikang & Wang, Bin, 2024. "Wind power forecasting based on ensemble deep learning with surrogate-assisted evolutionary neural architecture search and many-objective federated learning," Energy, Elsevier, vol. 308(C).
9. Ahmed S. Alahmed & Audun Botterud & Saurabh Amin, 2026. "Optimal Scheduling of Electricity and Water in Renewable-Colocated Desalination Plants," Papers 2601.02243, arXiv.org, revised Sep 2026.
10. Arooj, Qumrish, 2024. "FedWindT: Federated learning assisted transformer architecture for collaborative and secure wind power forecasting in diverse conditions," Energy, Elsevier, vol. 309(C).
11. Pu, Chuanqing & Fan, Feilong & Tai, Nengling & Liu, Songyuan & Yu, Jinming, 2026. "A hybrid strategy for probabilistic forecasting and trading of aggregated wind-solar power: Design and analysis in HEFTCom2024," International Journal of Forecasting, Elsevier, vol. 42(3), pages 736-751.
12. Ye, Feng & Miles, Travis & Aziz Ezzat, Ahmed, 2025. "Improved spatio-temporal offshore wind forecasting with coastal upwelling information," Applied Energy, Elsevier, vol. 380(C).
13. Han, Chanok & Vinel, Alexander, 2022. "Reducing forecasting error by optimally pooling wind energy generation sources through portfolio optimization," Energy, Elsevier, vol. 239(PB).
14. Zhang, Liwenbo & Yang, Yuexing & Wu, Yupeng, 2026. "Review of deep learning-based ground-sky imagery method for intra-hour solar irradiance forecasting: Workflow and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 239(C).
15. Yang, Dazhi & Kleissl, Jan, 2023. "Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1640-1654.
16. Wen, Honglin, 2024. "Probabilistic wind power forecasting resilient to missing values: An adaptive quantile regression approach," Energy, Elsevier, vol. 300(C).
17. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
18. González-Sopeña, J.M. & Pakrashi, V. & Ghosh, B., 2021. "An overview of performance evaluation metrics for short-term statistical wind power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
19. Mayer, Martin János & Yang, Dazhi, 2022. "Probabilistic photovoltaic power forecasting using a calibrated ensemble of model chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
20. Nasery, Praanjal & Aziz Ezzat, Ahmed, 2023. "Yaw-adjusted wind power curve modeling: A local regression approach," Renewable Energy, Elsevier, vol. 202(C), pages 1368-1376.
21. Zhang, Hanyu & Zandehshahvar, Reza & Tanneau, Mathieu & Van Hentenryck, Pascal, 2025. "Weather-informed probabilistic forecasting and scenario generation in power systems," Applied Energy, Elsevier, vol. 384(C).
22. Rao, Amar & Kumar, Satish & Karim, Sitara, 2024. "Accelerating renewables: Unveiling the role of green energy markets," Applied Energy, Elsevier, vol. 366(C).
23. Li, Yang & Wang, Ruinong & Li, Yuanzheng & Zhang, Meng & Long, Chao, 2023. "Wind power forecasting considering data privacy protection: A federated deep reinforcement learning approach," Applied Energy, Elsevier, vol. 329(C).
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25. Cramer, Eike & Witthaut, Dirk & Mitsos, Alexander & Dahmen, Manuel, 2023. "Multivariate probabilistic forecasting of intraday electricity prices using normalizing flows," Applied Energy, Elsevier, vol. 346(C).
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27. Eamonn Organ & Maeve Upton & Denis Allard & Lionel Benoit & James Sweeney, 2026. "Enhancing the Accuracy of Spatio‐Temporal Models for Wind Speed Prediction by Incorporating Bias‐Corrected Crowdsourced Data," Environmetrics, John Wiley & Sons, Ltd., vol. 37(2), March.
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