Análise comparativa de técnicas meta-heurísticas empregadas no seguimento da máxima potência em sistemas fotovoltaicos

Abstract

Considering that photovoltaic systems may be subject to partial shading conditions, presenting several maximum power points (MPP), being one global point (GMPP), and the remaining local points (LMPP), this work presents a comparative analysis between metaheuristic methods capable to deal with optimization problems related to the maximum power point tracking (MPPT). The comparative analysis will be conducted through the evaluation of the following metaheuristic techniques Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), optimization by the algorithm of Gray Wolf Optmizer (GWO), Fish Swarm Algorithm (FSA), Artificial Bee Colony (ABC) and the algorithm based in the Bats behavior (BAT), the techniques are evaluated considering the static and dynamic system performance in the search for GMPP in both uniform solar irradiation and partial shading conditions. The MPPT techniques are evaluated employing a DC-DC step-up converter, in which the algorithm through the duty cycle controls the voltage of the PV array. By means of simulation results, the MPPT techniques are evaluated and compared to each other considering five different test scenarios and the following criteria: time to reach the GMPP, efficiency in tracking, tracking factor and time spent in simulation.