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

Abstract

Adequate assessment of solar radiation data is crucial for planning and designing solar energy systems. However, a major challenge facing solar energy technologies is the availability of solar radiation data at the specific area of interest. In this paper solar radiation and sunshine duration data from 29 stations in Zimbabwe were used to generate both monthly and annual Angstrom-Prescott (A-P) type coefficients, a and b, that are location based. The coefficients were developed using linear correlation between the clearness index and sunshine duration. The adaptation relationship between satellite and ground-measured irradiation had an R2 of 0.6738. The correlation between the clearness index and the sunshine duration in most of the stations was fairly high with the highest coefficient of determination, R2, of 0.9030. The A-Pregression coefficient, a, generated using the data from each station ranged between 0.2252 and 0.3976, whereas the regression coefficient, b, ranged between 0.3218 and 0.6265. The estimated and measured values of global solar radiation, He, and Hm, respectively from each station were compared using the mean absolute percentage error (MAPE), the root mean square error (RMSE), the mean absolute error (MAE) and the relative standard error (RSE). The MAE values for the models ranged from 0.5438 MJ/m2 to 2.2845 MJ/m2. The MAPE indicated a range between 2.5642 % and 10.334 %. The RSE ranged between 0.0346 % and 0.1537% while the RMSE for the models ranged from 0.7360 MJ/m2 to 2.9454 MJ/m2. The statistical indicators showed results that were within the recommended range for solar radiation predicting models from similar studies.