Improving the performance of PV system using genetically-tuned FLC based MPPT

In this paper, an optimization of fuzzy logic controller (FLC) based maximum power point tracking (MPPT) using genetic algorithm (GA) is performed. The optimization process is performed by tuning the FLC's data base (DB) represented by parameters of membership functions (MFs) used. The tuning process is based on an objective function that is defined in terms of the statistic quantity named integral of squared error (ISE). In this paper, the photovoltaic (PV) system including PV module BP SX150S, ideal buck-boost DC-DC converter, MPPT, and resistive load of 6 Ω is used. The simulation performances of the proposed MPPT is evaluated and compared with the pre-tuned FLC based MPPT method using Matlab/Simulink package. The simulation results of the proposed method is quite promising and encouraging in which the PV system is capable of harvesting more solar power compared to pre-tuned FLC MPPT method.