Statistical Modelling Of Global Solar Radiation On Horizontal Surface Using Monthly Means Daily Sunshine Hours And Some Climatic Variables For Zamfara State, Nigeria

Abstract

In this study, four empirical models on the basis of linear Angstrom-Prescotte model for predicting monthly mean daily global solar radiation on horizontal surface were developed, correlating solar radiation to climatic parameters of sunshine hours, temperature and relative humidity. The models were used to predict Global solar radiation, an average solar radiation of 16.9690 and maximum and minimum of 19.2647 and 13.5222 C 0 were respectively predicted. For validation and the accuracy of the models, statistical coefficient of determination, R 2 , mean percentage error, (MPE), mean bias error, (MBE), and root mean square error (RMSE) were used. The result showed that, model correlating solar radiation with Sunshine hours, temperature and relative humidity gives the best fit for the study location with R 2 = 83.89%, that was;

Angstrom-Prescott Type Models for Predicting Solar Irradiation for Different Locations in Zimbabwe

“…The RSE for the models was found to be between 0.0346 % and 0.1537% showing very low values of the standard error relative to the estimated values, hence indicating high degrees of accuracy of estimation correlations in the models similar to values of RSE found in other studies by [26] and [84]. The RMSE for the models ranged from 0.7360 MJ/m 2 to 2.9454 MJ/m 2 and these values are within the recommended range for excellent solar predicting models from other similar studies [51] and [89], hence indicating good short-term predicting capabilities for all the models. As shown in Fig.…”

“…MAPE values less than 10 % indicate a good precision model [17] and [88]. The closer the RMSE values are to zero the more accurate the model is and a value of RMSE equals zero is the ideal value [17], [51] and [89].…”