Particle swarm optimization approach to determine all parameters of the photovoltaic cell

In order to describe the behavior and the performance of the photovoltaic modules we can found in the literature different equivalent circuit models such us: single diode model (SDM), double diode model (DDM), three diode model (TDM). Almost of the authors obtained that the SDM is the best solution to describe the electrical characterization of the PV modules. The PV parameters can be extracted by three common approaches: Analytical based on the derivation of mathematical equations, Numeric or iterative usually use non-linear optimization techniques, among all the technique the Newton Raphson is widely used. The last one is meta-heuristic approach characterized by their global search point and their soft computing algorithms. The aim of this study is to explore and discuss the behavior of the single-diode model, which require five parameters are estimated using Particle Swarm Optimization approach. The performance of this method is evaluated using the experimental values of R.T.C France PV cell at irradiation G = 1000 W/m2 and at temperature T = 33 °C. The obtained results are also compared with results of the others computing approach. After this study, we can conclude that the proposed PSO method has the best performance because the RMSE obtained using this approach is around the 1.73.10−4 A and low than those obtained through all compared algorithms.