Abstract
It is important to have accurate knowledge on global solar radiation for optimum design of solar energy conversion systems. However, global solar radiation measurement is very rare in meteorological stations in all around the world. Hence, modeling global solar radiation is an crucial issue to fill the gaps in database and to estimate global solar radiation in places where global solar radiation measurement is not available.This paper presents a detailed description and analysis of various global solar radiation modeling methods. The efficiency and accuracy of ten models from different functions to estimate daily solar radiation in EMR are investigated. Also an optimized model based on Artificial Neural Network (ANN) method and Angström-Prescott model for the estimation of daily global solar radiation are presented. The essence of this paper is to investigate the performance of the ANN model and Angström-Prescott model in order to ensure the most feasible solution for estimating daily global solar radiation for Eastern Mediterranean Region (EMR) of Turkey. 11 years solar radiation data from 4 stations are utilized in training and testing of developed ANN model and parametric model which is based on Angström-Prescott method. In order to ensure a simple application of the model that most accurately predicts the desired target value, a new graphical user interface is developed with MATLAB GUI.
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