Afshin Lashkar Ara - Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran
rahil hosseini - Department of Computer Engineering, Shahr‐e‐Qods Branch, Islamic Azad University, Tehran, Iran
Hajar Bagheri Tolabi - Department of Electrical Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran

In this paper, a novel approach for the estimation of global solar irradiance is proposed based on a combination of empirical correlation and ant colony optimization. Empirical correlation has been used to estimate monthly average of daily global solar irradiance on a horizontal surface. The Ant Colony Optimization (ACO) algorithm has been applied as a swarm-intelligence technique to tune the coefficients of linear and nonlinear empirical models. . The performance of the models is investigated for the estimation of global solar irradiance at four different climatic regions of Iran based on statistical indicators like coefficient of determination (R۲) and root mean square error (RMSE). The results obtained from the proposed model are superior in comparison with the other well established models.

Ant colony optimization (ACO), Empirical Models, Global solar irradiance, Intelligent models