Prediction of diffuse solar radiation based on multiple variables in China
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DOI: 10.1016/j.rser.2018.12.029
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Cited by:
- Xie, Yu & Sengupta, Manajit & Habte, Aron & Andreas, Afshin, 2022. "The “Fresnel Equations” for Diffuse radiation on Inclined photovoltaic Surfaces (FEDIS)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
- Feng, Yu & Hao, Weiping & Li, Haoru & Cui, Ningbo & Gong, Daozhi & Gao, Lili, 2020. "Machine learning models to quantify and map daily global solar radiation and photovoltaic power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
- Yang, Liu & Cao, Qimeng & Yu, Ying & Liu, Yan, 2020. "Comparison of daily diffuse radiation models in regions of China without solar radiation measurement," Energy, Elsevier, vol. 191(C).
- Bakirci, Kadir, 2021. "Prediction of diffuse radiation in solar energy applications: Turkey case study and compare with satellite data," Energy, Elsevier, vol. 237(C).
- Lu, Yunbo & Wang, Lunche & Zhu, Canming & Zou, Ling & Zhang, Ming & Feng, Lan & Cao, Qian, 2023. "Predicting surface solar radiation using a hybrid radiative Transfer–Machine learning model," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
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Keywords
diffuse solar radiation; multiple variables; diffuse fraction; model comparison;All these keywords.
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