Photovoltaic maximum power point tracking under dynamic partial shading changes by novel adaptive particle swarm optimization strategy

Abstract

Maximum power point tracker (MPPT) is vital device in the Photovoltaic (PV) system because it can increase the generated power considerably. Partial shading conditions (PSCs) on the PV array generates many peaks in the P-V curve of PV array. Metaheuristic techniques like particle swarm optimization (PSO) have the ability to track the global peak (GP) at any operating conditions. PSO technique can track the GP but once the shading pattern (SP) changes, the value and location of the new GP will change and may PSO cannot catch the new GP because all particles are busy around the previous GP. This problem is classified into two conditions: the first condition if the GP change its location and value suddenly, the second condition occurs when the GP changes its value gradually and still in same place. The first problem is solved by reinitializing the particles. The second problem is solved using a new adaptive strategy that has not been treated or adopted in any literature before. The results obtained prove the superiority of the new proposed strategy in always catching GP in dynamic change PSCs.