Evaluation of the regression coefficients for South Africa from solar radiation data

Abstract

The knowledge of solar radiation in this dispensation is crucial. The lack of grid lines in the remote rural areas of South Africa necessitates the use of solar energy as an alternative energy resource. Solar radiation data is one of the primary factors considered for the installation of renewable energy devices and they are very useful for solar technology designers and engineers. In some developing countries, estimation of solar radiation becomes a challenge due to the lack of weather data. This scenario is also applicable to South Africa (SA) wherein there are limited weather stations and hence there is a dire need of estimating the global solar radiation data for all climatic regions. Using a five year global solar radiation (𝐻) and bright sunshine (𝑆) data from the Agricultural Research Council (ARC) and South African Weather Service (SAWS) in SA, linear Angstrom – Prescott solar empirical model was used to determine regression coefficients. MATLAB interface was used whereby the linear regression plots were drawn. Annual empirical coefficients of 22 stations were determined and later the provincial values. The range of the regression coefficients, a and b were 0.216 – 0.301 and 0.381 – 0.512 respectively. The 2006 estimated global solar radiation per station in a province calculated from the modified models were compared with the observed and statistically tested. The root mean square errors were less than 0.600 MJm−2day−1 while the correlation relation ranged from 0.782 – 0.986 MJm−2day−1. The results showed the regression coefficients performed well in terms of prediction accuracy.