A novel global MPPT technique based on squirrel search algorithm for PV module under partial shading conditions

Abstract

The partial shading condition (PSC) makes it challenging for the PV system to harvest maximum power via maximum power point tracking (MPPT). Various MPPT algorithms based on bio-inspired optimization methods were proposed in the literature. The mechanism employed by these algorithms varies from one to another, making them perform differently when tracking the GMPP. This paper introduces a novel MPPT technique based on the improved squirrel search algorithm (ISSA). The performance of the proposed ISSA improved the tracking time by 50% in comparison with the conventional SSA algorithm. Similarly, the proposed method has also been compared with popular Genetic algorithm (GA), and particle swarm optimization (PSO). The results proved the ability of the proposed algorithm in tracking the GMPP with faster convergence and fewer power oscillations in comparison. The feasibility and effectiveness of the proposed ISSA based MPPT have been validated experimentally, and the results clearly demonstrate its capability in tracking the GMPP with an average efficiency of 99.48% and average tracking time of 0.66 s.