Enhanced energy output from a PV system under partial shaded conditions through grey wolf optimizer

Abstract

Due to its several powerful characteristics, the Grey Wolf Optimization (GWO) algorithm has recently become widely used in numerous optimization problems. In photovoltaic (PV) systems, power-voltage (P–V) curves present multiple maxima in case of partial shadow or modules mismatch which can be viewed as an optimization problem. In this paper, a GWO-based maximum power tracking (MPPT) algorithm for PV systems operating under partial shading conditions (PSCs) is proposed. With a direct control method, the proposed GWO-based MPPT allows successfully catching the global maximum power point (GMPP) of the PV array in case of uniform and non-uniform solar irradiation. To evaluate the effectiveness of the proposed MPPT scheme, a co-simulation combining Matlab/Simulink™ and Cadence/Pspice™ software environments is carried out and tested under various static and dynamic shading conditions. Furthermore, the tracking performance is compared with that of the particle swarm optimization (PSO) and classical perturb and observe (P&O) based MPPT methods under transient PSCs and also under inhomogeneous real conditions of Algerian sky. The simulation results have demonstrated the satisfactory performances of the proposed approach in terms of tracking efficiency and tracking speed over the other MPPT methods.

Keywords

• PV systems
• MPPT
• Grey wolf optimizer
• Partially shaded conditions
• Boost converter
• Particle swarm optimization