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Title Estimation of global solar radiation using empirical models
Authors Onyeka, V.O.
Nwobi-Okoye, C.C.
Okafor, O.C
Madu, K.E.
Mbah, O.M.
ORCID
Keywords renewable energy
global solar radiation
artificial neural network
statistical tests
Type Article
Date of Issue 2021
URI https://essuir.sumdu.edu.ua/handle/123456789/87422
Publisher Sumy State University
License Creative Commons Attribution 4.0 International License
Citation Onyeka V. O., Nwobi-Okoye C. C., Okafor O. C., Madu K. E., Mbah O. M. (2021). Estimation of global solar radiation using empirical models. Journal of Engineering Sciences, Vol. 8(2), pp. G11-G24, doi: 10.21272/jes.2021.8(2).g2
Abstract The dearth of solar radiation data availability has necessitated the development of several mathematical models for estimating global solar radiation (GSR) of regions using the readily available meteorological data of the region. This study was centered on estimating the GSR of the Ihiala region in Sub-Saharan Africa using empirical models. For the last ten years, meteorological data from the Nigerian Meteorological Agency (NIMET) were used. The sunshine-based equation, temperature-based equation, and multivariate polynomial equations were the empirical models employed to estimate the GSR of the region. The performance of the seven models was determined using statistical measures. From the results obtained, the seven models had their respective P-values all less than 5 % significant level for a confidence interval of 95 %. Thereby attesting their suitability for GSR estimation of the region is needed. Also, from the other statistical tools employed, the considered multivariate model had better estimation performance than the other models. Therefore, the considered multivariate model is suitable for estimating the GSR of the Ihiala region in Sub-Saharan Africa.
Appears in Collections: Journal of Engineering Sciences / Журнал інженерних наук

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