Models for prediction of global solar radiation on horizontal surface for Akure, Nigeria

Abstract

The estimation of global solar radiation continues to play a fundamental role in solar engineering systems and applications. This paper compares various models for estimating the average monthly global solar radiation on horizontal surface for Akure, Nigeria, using solar radiation and sunshine duration data covering years 1981 to 1995. The analysis was performed using Angstrom models, two dimensional principal component analysis (PCA) and adaptive neuro-fuzzy inference system (ANFIS). The performance of the models were tested using statistical indicators such as mean bias error (MBE), mean percentage error (MPE), root mean square error (RMSE) and correlation coefficient (CC). The results indicated that ANFIS and linear regression analysis provide relatively higher degree of prediction, with the performance of ANFIS slightly better.

Keywords: Angstrom model, fuzzy logic system, principal component analysis, regression analysis, solar radiation, sunshine duration