Self Adaptive Particle Swarm Optimization Based Global Maximum Point Tracking Algorithm for Photovoltaic Systems

The generated output power of photovoltaic (PV) array reduces drastically due to partial shading (PS). This reduction in output power mainly depends on the type of shading, shading area and array configurations. This performance can be improved by the bypass diode. These bypass diode exhibit multiple peaks in electrical characteristics (P-V & I-V curves). Because of these peaks, the global maximum power point (GMPP) tracking becomes difficult. Hence, conventional algorithms are unable to give a satisfactory result. Although particle swarm optimization (PSO) algorithm can track the GMPP, its dynamic performance is poor. Therefore in this paper, Self Adaptive PSO based GMPP tracking algorithm has been proposed. Simulations are performed under two different shading conditions and compared with PSO based optimization algorithm. The result shows the advantages of the algorithm in terms of tracking time and number of oscillations and tracking efficiency.