Design and Simulation of a PV System Controlled through a Hybrid INC-PSO Algorithm using XSG Tool

Abstract

This paper details the development of a hybrid algorithm for maximum power point tracking (MPPT) used for large PV systems under real conditions. In this algorithm, the incremental conductance algorithm (INC) is used in the initial phase of tracking, and the particle swarm optimization method (PSO) in the second phase. The methodology was simulated using the Xilinx System Generator (XSG) tool. The integration of artificial intelligence into the INC algorithm allows for faster convergence to the global maximum power point (GMPP). Simulation results prove that the proposed algorithm increases the efficiency, corrects the tracking direction and quickly reaches the steady state without oscillations.