Estimation of Measured Global Solar Radiation by Artificial Neural Networks for Mersin / Turkey and Comparison with Common Solar Radiation Models

Abstract

In this study, the daily total global solar radiation values measured for Mersin between April 2017 and March 2018 were modeled using artificial neural networks and the performance of estimating daily total global solar radiation values of the common models in the literature was investigated. Daily average air temperature, relative humidity, wind speed, sunshine duration, and cloud cover data are obtained from the Turkish State Meteorological Service and solar radiation values are measured with a pyranometer. As a result, Model 37 (Zhang and Huang) showed the best prediction performance among the models examined, with the coefficient of determination (R2) being 0.83.

Keywords

• Prediction of global solar radiation
• Solar radiation model Artificial Neural Networks Mersin
• Solar radiation model
• Artificial Neural Networks Mersin
• Artificial Neural Networks
• Mersin