Estimating daily Global solar radiation with graphical user interface in Eastern Mediterranean region of Turkey

H. Başak Yıldırım*, Özgür Çelik, Ahmet Teke, Burak Barutçu

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

54 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)1528-1537
Number of pages10
JournalRenewable and Sustainable Energy Reviews
Publication statusPublished - Feb 2018

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Ltd


  • ANN
  • Empirical models
  • Global solar radiation assessment


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