A critical analysis of PSO and its variations applied to MPPT for PV Systems under Partial Shading Condition

The maximum power that a photovoltaic system is able to provide depends on the climate conditions in which it is submitted. In order to extract the maximum available energy from the system, independent of weather conditions, a Maximum Power Point Tracking (MPPT) system must be used. Several methods can be used to track the maximum power, but the efficiency of tracking depends on the chosen technique. Moreover, when the array is under a partial shading condition, new power peaks arise, which makes some techniques unfeasible. In this paper, an analysis of the evolutionary algorithm Particle Swarm Optimization (PSO) as an MPPT method under partial shading condition is evaluated. Simulations of this technique and its variations, such as DPSO, in different partial shading patterns are performed. As the other MPPT techniques, the PSO and its variations have inconveniences that decrease their efficiency under partial shading conditions. Among these, the wrong power measurement and blocking of particles in DPSO need to be considered because they result in high power losses. To avoid these conditions, computational adjustments are proposed and their efficiency is analyzed through simulations.