Maximum Power Tracking of Photovoltaic System Under Partial Shading Based on PACO-BFOA

In allusion to the fact that traditional maximum power point tracking algorithms are easy to fall into local maximum power point, for this reason, a polymorphic ant colony-bacterial foraging optimization algorithm (PACO-BFOA) was proposed to realize the maximum power output of the photovoltaic system under partial shading condition (abbr. PSC). On the basis of traditional ant colony algorithm the proposed algorithm led in the pheromone diffusion mechanism, the concept of polymorphic ant colony and the chemotactic behavior of bacteria to make both global development and local exploration ability of this algorithm enhanced. Under three different environments, i.e., constant irradiance, abruptly varying irradiance, and slowly varying irradiance, the simulation verification on the effectiveness of the PACO-BFOA was carried out. Verification results show that by use of the proposed algorithm the global maximum power point can be online fast and steady searched out under the conditions of partial shading and varying solar irradiation.