Comparative Analysis of Empirical and AI-Supported Models in Global Solar Radiation Prediction for İzmir Province
Year: 2025
Type: article
Abstract: In this study, the performances of different models that can be used to predict global solar radiation for İzmir province were analyzed comparatively. Using ATATEK-Solar software, 14 empirical models commonly used in the literature and a newly developed AI-supported model were tested. Each model was analyzed using three different optimization algorithms (Nelder-Mead Simplex, Pattern Search, Simulated Annealing). Long-term average meteorological data obtained from Turkish State Meteorological Service were used. According to the analysis results, Model 15 performed the most successful predictions with RMSE:0.1451 and R²:0.9995 values. This was followed by Model 5 with RMSE:0.2016 and R²:0.9990 values and Model 6 with RMSE:0.2017 and R²:0.9990 values. When model performances were examined on a monthly basis, it was observed that the lowest prediction errors occurred in spring and summer months. As a result of the study, it is recommended to use Model 15 in evaluating the solar energy potential of İzmir province and system design.
Author: Ahmet SÜSLÜ
Institution: Isparta University of Applied Sciences
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408806743