On the effects of hyper-parameters adjustments to the PSO-GMPPT algorithm for a photovoltaic system under partial shading conditions

This paper exploits the performance of the particle swarm optimization (PSO) algorithm for a photovoltaic system under partial shading condition (PSC). Essentially our main contribution consists on analyzing the hyper-parameters adjustment of the PSO algorithm to determine the minimum particle numbers, such that the assertiveness to identify the Global Maximum Power Point (GMPP) be higher than 99%. The database was obtained throughout 5760 simulations based on different test cases. From these test cases, the PSC was applied in 2880 simulations. In the previous work, it was shown the best results based on 5 particles. In this update version, it is also shown the best results for 3, 7 and 9 particles, together with a comparison among them. Furthermore, this paper also presents the simulation results to evaluate the performance of the developed algorithm under transient- and steady-state conditions