Maximum Power Extraction from Solar Photovoltaic Strings Using Grey Wolf Optimization Technique Under Partial Shading Condition

Abstract

This paper gives the realization of Grey Wolf Optimization (GWO) method for the design of maximum power extraction techniques incorporated in solar photovoltaic system to extract maximum energy under varying irradiation conditions. The Grey Wolf Optimization is a novel technique which conquers the confines for instance, poor conversion efficiency, fluctuations, and transients as detected in perturb & observe (P&O) and advanced particle swarm optimization technique. GWO is a recently developed population-based swarm intelligence technique which has already shown its popularity in providing superior quality results for ample types of optimization problems. The hunting strategy and position updating strategy of the wolves balanced by some crucial mathematical parameters provides a rich diversification and intensification methodology in mapping the search space for the best possible solution. Moreover, GWO eliminates the possible demerits of getting stuck in local minima and a larger number of tuning parameters. Hence GWO is prioritized over other meta-heuristic algorithms. The projected format is considered for a PV array beneath partial shading which display several peaks and its tracking concert is related to that of two MPPT algorithms , namely perturb & observe, Particle swarm optimization technique . The projected GWO tracking algorithm is carried out on a photovoltaic system using MATLAB/Simulink. As of the acquired MATLAB/Simulink end results, it is evaluated that the suggested GWO algorithm beats both Perturb&Observe and Particle swarm optimization (PSO) techniques.