An Improved Light Spectrum Optimizer for Parameter Identification of Triple-Diode PV Model

Abstract

Over the last few decades, researchers have paid attention to finding an effective and efficient metaheuristic algorithm that can determine the ideal parameters for PV models. In this study, to determine the TDM’s nine unknown parameters, we will examine the efficacy of a recently proposed metaheuristic algorithm called light spectrum optimizer (LSO). To further enhance the effectiveness of LSO in estimating those unknown parameters, a new improved variant called ILSO is developed. This variant employs LSO in conjunction with two newly developed update systems to improve its exploration and exploitation operators. We compare the best fitness value, worst fitness value, average fitness, standard deviation, and p-value returned by the Wilcoxon rank-sum test obtained by LSO and ILSO to those of three recently published competitors when estimating the nine unknown parameters for the Photowatt-PWP201 module and the RTC France solar cell. The experimental findings show that ILSO is the most efficient.