Parameters Estimation of Photovoltaic Modules Using Differential Evolution Metaheuristic Method

Abstract

This paper presents the analysis of the differential evolution (DE) metaheuristic method, which is used to estimate some parameters employed in the equivalent electrical circuit that represents the photovoltaic (PV) cell model. The DE algorithm is an evolutionary algorithm that can be designed to search global optimal points with fast convergence time and present accurate results, requiring few control variables to be set. The accuracy of reproducing the characteristics of the PV module depends on the knowledge of some PV cell model parameters, such as series and shunt resistances, diode ideality factor, and diode reverse saturation current. Once the referred parameters are not usually given in the manufacturers' datasheet, their determination can be achieved by the DE algorithm, employing data and the current-voltage (I-V) characteristic curve provided by the PV module manufacturers. The technique is designed to minimize the error between the reference I-V curve and the I-V curve reproduced by the DE algorithm. Through simulation results, the feasibility of the DE algorithm to estimate the desired parameters of a PV cell is validated, and the algorithm's performance to reach the best solution with fast convergence and a small iteration number is evaluated.