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 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.
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Last update: 2021-03-05 02:55:24
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Last update: 2021-03-05 02:55:24
-
Evaluation of various global solar radiation models for Nigeria
Michael S. Okundamiya, Joy O. Emagbetere, Emmanuel A. Ogujor. International Journal of Green Energy, 13 (5), 2016. doi: 10.1080/15435075.2014.968921 -
Size optimization of a hybrid photovoltaic/fuel cell grid connected power system including hydrogen storage
M.S. Okundamiya. International Journal of Hydrogen Energy, 2020. doi: 10.1016/j.ijhydene.2020.11.185 -
Empirical models for estimating the global solar radiation of Jubail Industrial City, the Kingdom of Saudi Arabia
Sheik Mujabar, Rao Chintaginjala Venkateswara. SN Applied Sciences, 3 (1), 2021. doi: 10.1007/s42452-020-04043-9

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