Abstract:
hstimating anct assessing the energy talling in a particular area 1s essential tor installers ot
renewable technologies. Different equations have been applied as the most reliable empir ical for
estimating global solar radiation(GSR) in different climatic conditions. The main objective of this
work is to estimate the global solar radiation of two stations namely, Mu tale and Messina found
in Vhembe District, Limpopo Province, South Africa. Four different methods (Random forest(RF)
regression, K-nearest neighour (K-NN), Support Vector Ma chines(SVM) and Extreme Gradient Boosting
mechanism(XGBoost)) is used to estimate the
GRS in this study. The RF model on Mutale station was found to be the best fitting model with R² =
0.9902, MSE = 0.4085 and RMSE = 0.6391, followed by XGB with R² = 0.9898, MSE = 0.4245 and RMSE =
0.6515. RF was also found to be the best for Messina station with R² = 0.9636, MSE = 0.1.4138 and
RMSE = 1.1890, followed by XGB model with R² = 0.9595, MSE = 1.5723 and RMSE = 1.2539. From the
results, it can be concluded that
RF is a better model for estimating GSR for different stations.
