Probabilistic solar power forecasting based on weather scenario generation
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DOI: 10.1016/j.apenergy.2020.114823
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- Moradzadeh, Arash & Moayyed, Hamed & Mohammadi-Ivatloo, Behnam & Vale, Zita & Ramos, Carlos & Ghorbani, Reza, 2023. "A novel cyber-Resilient solar power forecasting model based on secure federated deep learning and data visualization," Renewable Energy, Elsevier, vol. 211(C), pages 697-705.
- Nabilah Mat Kassim & Sathiswary Santhiran & Ammar Ahmed Alkahtani & Mohammad Aminul Islam & Sieh Kiong Tiong & Mohd Yusrizal Mohd Yusof & Nowshad Amin, 2023. "An Adaptive Decision Tree Regression Modeling for the Output Power of Large-Scale Solar (LSS) Farm Forecasting," Sustainability, MDPI, vol. 15(18), pages 1-12, September.
- Kaiyan Wang & Haodong Du & Rong Jia & Hongtao Jia, 2022. "Performance Comparison of Bayesian Deep Learning Model and Traditional Bayesian Neural Network in Short-Term PV Interval Prediction," Sustainability, MDPI, vol. 14(19), pages 1-27, October.
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- Paletta, Quentin & Hu, Anthony & Arbod, Guillaume & Lasenby, Joan, 2022. "ECLIPSE: Envisioning CLoud Induced Perturbations in Solar Energy," Applied Energy, Elsevier, vol. 326(C).
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Keywords
Probabilistic solar power forecasting; Weather scenario generation; Gibbs sampling; Gaussian mixture model; Copula;All these keywords.
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