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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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Onyeka_jes_2_2021.pdf | 437.92 kB | Adobe PDF | 120992596 |
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