A radiant shift: Attention-embedded CNNs for accurate solar irradiance forecasting and prediction from sky images
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DOI: 10.1016/j.renene.2024.121133
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References listed on IDEAS
- Luo, Xing & Zhang, Dongxiao & Zhu, Xu, 2021. "Deep learning based forecasting of photovoltaic power generation by incorporating domain knowledge," Energy, Elsevier, vol. 225(C).
- Kong, Weicong & Jia, Youwei & Dong, Zhao Yang & Meng, Ke & Chai, Songjian, 2020. "Hybrid approaches based on deep whole-sky-image learning to photovoltaic generation forecasting," Applied Energy, Elsevier, vol. 280(C).
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- Ukwuoma, Chiagoziem C. & Cai, Dongsheng & Bamisile, Olusola & Yin, Hongbo & Nneji, Grace Ugochi & Monday, Happy N. & Oluwasanmi, Ariyo & Huang, Qi, 2024. "An attention fused sequence -to-sequence convolutional neural network for accurate solar irradiance forecasting and prediction using sky images," Renewable Energy, Elsevier, vol. 237(PB).
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Keywords
Deep learning; CNN; Attention mechanism; Sky image sequence; Solar forecasting;All these keywords.
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