Estimating the daily global solar radiation spatial distribution from diurnal temperature ranges over the Tibetan Plateau in China
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DOI: 10.1016/j.apenergy.2013.02.053
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- Hassan, Gasser E. & Youssef, M. Elsayed & Mohamed, Zahraa E. & Ali, Mohamed A. & Hanafy, Ahmed A., 2016. "New Temperature-based Models for Predicting Global Solar Radiation," Applied Energy, Elsevier, vol. 179(C), pages 437-450.
- Zhang, Jianyuan & Zhao, Li & Deng, Shuai & Xu, Weicong & Zhang, Ying, 2017. "A critical review of the models used to estimate solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 314-329.
- Jiang, Chengcheng & Zhu, Qunzhi, 2023. "Evaluating the most significant input parameters for forecasting global solar radiation of different sequences based on Informer," Applied Energy, Elsevier, vol. 348(C).
- Jiang, Hou & Lu, Ning & Qin, Jun & Yao, Ling, 2021. "Hierarchical identification of solar radiation zones in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
- Zang, Haixiang & Jiang, Xin & Cheng, LiLin & Zhang, Fengchun & Wei, Zhinong & Sun, Guoqiang, 2022. "Combined empirical and machine learning modeling method for estimation of daily global solar radiation for general meteorological observation stations," Renewable Energy, Elsevier, vol. 195(C), pages 795-808.
- Jiandong Liu & Tao Pan & Deliang Chen & Xiuji Zhou & Qiang Yu & Gerald N. Flerchinger & De Li Liu & Xintong Zou & Hans W. Linderholm & Jun Du & Dingrong Wu & Yanbo Shen, 2017. "An Improved Ångström-Type Model for Estimating Solar Radiation over the Tibetan Plateau," Energies, MDPI, vol. 10(7), pages 1-28, July.
- Teke, Ahmet & Yıldırım, H. Başak & Çelik, Özgür, 2015. "Evaluation and performance comparison of different models for the estimation of solar radiation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1097-1107.
- 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).
- Ghimire, Sujan & Nguyen-Huy, Thong & AL-Musaylh, Mohanad S. & Deo, Ravinesh C. & Casillas-Pérez, David & Salcedo-Sanz, Sancho, 2023. "A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction," Energy, Elsevier, vol. 275(C).
- Wang, Lunche & Kisi, Ozgur & Zounemat-Kermani, Mohammad & Salazar, Germán Ariel & Zhu, Zhongmin & Gong, Wei, 2016. "Solar radiation prediction using different techniques: model evaluation and comparison," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 384-397.
- Koo, Choongwan & Li, Wenzhuo & Cha, Seung Hyun & Zhang, Shaojie, 2019. "A novel estimation approach for the solar radiation potential with its complex spatial pattern via machine-learning techniques," Renewable Energy, Elsevier, vol. 133(C), pages 575-592.
- Halawa, Edward & GhaffarianHoseini, AmirHosein & Hin Wa Li, Danny, 2014. "Empirical correlations as a means for estimating monthly average daily global radiation: A critical overview," Renewable Energy, Elsevier, vol. 72(C), pages 149-153.
- Amrouche, Badia & Le Pivert, Xavier, 2014. "Artificial neural network based daily local forecasting for global solar radiation," Applied Energy, Elsevier, vol. 130(C), pages 333-341.
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Keywords
Global solar radiation; Spatial distribution; Bristow–Campbell model; PRISM; Tibetan Plateau;All these keywords.
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