Estimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models

Lashkar Ara, Afshin; Hosseini, Rahil; Bagheri Tolabi, Hajar

doi:10.30501/jree.2016.70093

Document Type : Research Article

Authors

¹ Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

² Department of Computer Engineering, Shahr‐e‐Qods Branch, Islamic Azad University, Tehran, Iran

³ Department of Electrical Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran

https://doi.org/10.30501/jree.2016.70093

Abstract

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 (R2) and root mean square error (RMSE). The results obtained from the proposed model are superior in comparison with the other well established models.

Keywords

References

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Estimation of Global Solar Irradiance Using a Novel combination of Ant Colony Optimization and Empirical Models

References

References

Volume 3, Issue 3August 2016Pages 59-66

Volume 3, Issue 3
August 2016
Pages 59-66