GMPPT approach for photovoltaic systems under partial shading conditions using a genetic algorithm

Abstract

In this paper a new global maximum power point tracking (GMPPT) approach is proposed for a photovoltaic (PV) module using a genetic algorithm (GA) system under partial shading conditions. The partial shading condition is one of the adverse phenomena that the PV system experiences, it is difficult to track true peaks because of existence of multiple peaks in a PV array (partially shaded based). The conventional GMPPT algorithms met in the literature, the initial value of reference is approximated arbitrarily for various conditions of irradiation and temperature and they can’t distinguish between the local and global peaks if partial shading occurs, what reduces the performances of the tracking of the point of optimal operation of PV systems. So, to improve these performances, we proposed a nonlinear based GMPPT method to estimate the initial optimal operating point. To compare with conventional GAs methods, the global peak (GP) tracking process is accomplished after follow the far fewer power perturbation steps. This approach made a possible to largely improve the GP tracking in the PV system, improve the accuracy of the GMPPT algorithms, and accelerate the convergence speed. This GMPPT method is checked for different shading profiles through the simulation and verification.