Introducing the best model for estimation the monthly mean daily global solar radiation on a horizontal surface (Case study: Algeria)

Abstract

Abstract In this study, 11 empirical models are developed correlating the monthly mean daily global solar radiation on a horizontal surface with monthly mean sunshine records and air temperature data for six Algerian cities (Algiers, Oran, Batna, Ghardaia, Bechar, and Tamanrasset). In order to indicate their performance, seven statistical parameters were introduced; coefficient of determination ( R 2 ), mean percent error (MPE), mean absolute percent error (MAPE), mean bias error (MBE), mean absolute bias error (MABE), and root mean square error (RMSE). The results obtained in this study confirm the previous studies, which have indicated that the sunshine based models are generally more accurate than air temperature based models. According to the results, the best performances are obtained by the cubic and the quadratic regression models for the six Algerian stations. Moreover, these two regression models can be used for the proposed generalized models for predicting the monthly mean global solar radiation in other Algerian locations in the absence of the measured solar radiation data.