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Statistical analysis of sunshine based global solar radiation (GSR) models for tropical wet and dry climatic Region in Nagpur, India: A case study

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  • Makade, Rahul G.
  • Jamil, Basharat

Abstract

In literature, numerous models are available to predict Global Solar Radiation (GSR) on a horizontal surface, which is predominantly a site-specific characteristic. Hence, a comparative study is required to predict GSR using a correct model for a particular site. The principal aim of the present work is to analyze the most precise model for estimation of monthly average daily global solar radiation (MADGSR) on a horizontal surface for the region of interest. In the current work, the performance of 300 existing sunshine based GSR models are compared using 15-year meteorological data for Tropical wet and dry climatic region of India. The accuracy of each model is tested using ten different statistical error tests. Further, the Global Performance Indicator (GPI) is used to rank the selected GSR models. According to results, the Ampratwum Model (Model 274, proposed for Marmul, Oman) has shown the best capability to estimate the GSR on a horizontal surface followed by Srivastava (Model 26, proposed for Kolkata, India) and Rensheng model (Model 282, proposed for China). The results of the present study are valuable for the developing countries and remote areas where very few metrological stations are available since the technological expenses are very high.

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  • Makade, Rahul G. & Jamil, Basharat, 2018. "Statistical analysis of sunshine based global solar radiation (GSR) models for tropical wet and dry climatic Region in Nagpur, India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 22-43.
    • Handle: RePEc:eee:rensus:v:87:y:2018:i:c:p:22-43
    DOI: 10.1016/j.rser.2018.02.001
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    3. Zang, Haixiang & Cheng, Lilin & Ding, Tao & Cheung, Kwok W. & Wang, Miaomiao & Wei, Zhinong & Sun, Guoqiang, 2020. "Application of functional deep belief network for estimating daily global solar radiation: A case study in China," Energy, Elsevier, vol. 191(C).

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