A Linear Regression Model for Global Solar Radiation on Horizontal Surfaces at Warri, Nigeria

The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel...

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Main Authors: Okundamiya, Michael S. (Author), Okpamen, Israel E. (Author)
Format: EJournal Article
Published: Center of Biomass & Renewable Energy, Diponegoro University, 2013-10-30.
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001 IJRED_UNDIP_5645_5026
042 |a dc 
100 1 0 |a Okundamiya, Michael S.  |e author 
100 1 0 |e contributor 
700 1 0 |a Okpamen, Israel E.  |e author 
245 0 0 |a A Linear Regression Model for Global Solar Radiation on Horizontal Surfaces at Warri, Nigeria 
260 |b Center of Biomass & Renewable Energy, Diponegoro University,   |c 2013-10-30. 
500 |a https://ejournal.undip.ac.id/index.php/ijred/article/view/5645 
520 |a The growing anxiety on the negative effects of fossil fuels on the environment and the global emission reduction targets call for a more extensive use of renewable energy alternatives. Efficient solar energy utilization is an essential solution to the high atmospheric pollution caused by fossil fuel combustion. Global solar radiation (GSR) data, which are useful for the design and evaluation of solar energy conversion system, are not measured at the forty-five meteorological stations in Nigeria. The dearth of the measured solar radiation data calls for accurate estimation. This study proposed a temperature-based linear regression, for predicting the monthly average daily GSR on horizontal surfaces, at Warri (latitude 5.020N and longitude 7.880E) an oil city located in the south-south geopolitical zone, in Nigeria. The proposed model is analyzed based on five statistical indicators (coefficient of correlation, coefficient of determination, mean bias error, root mean square error, and t-statistic), and compared with the existing sunshine-based model for the same study. The results indicate that the proposed temperature-based linear regression model could replace the existing sunshine-based model for generating global solar radiation data.  
540 |a https://creativecommons.org/licenses/by-sa/4.0 
546 |a eng 
690 |a air temperature; empirical model; global solar radiation; regression analysis; renewable energy; Warri 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n International Journal of Renewable Energy Development; Vol 2, No 3 (2013): October 2013; 121-126 
786 0 |n 2252-4940 
787 0 |n https://ejournal.undip.ac.id/index.php/ijred/article/view/5645/5026 
856 4 1 |u https://ejournal.undip.ac.id/index.php/ijred/article/view/5645/5026  |z Get Fulltext