Fast and improved PSO (FIPSO)-based deterministic and adaptive MPPT technique under partial shading conditions

Abstract

Partial shading in photovoltaic (PV) power generating systems is practically unavoidable and is a menace to the PV system. Non-uniform shading can be caused due to clouds, tree branches, buildings or other nearby items. The non-linear output characteristics of a PV source varies with temperature and solar insolation. During partial shading condition, the conventional hill-climbing methods of maximum power point tracking (MPPT) prove to be inefficient. In partial shading, the power-voltage curve exhibits multiple peaks. Conventional MPPT methods get stuck on one of the local maxima and fail to attain the global maximum power point (GMPP). Particle swarm optimisation (PSO) has proved to be a very accurate and powerful technique to find GMPP. In this study, the authors improved the conventional PSO by reducing swarm size, as well as, the number of iterations to achieve MPP at a fast pace with remarkable accuracy, thus making the system more efficient with less computational effort. Simulation and hardware implementation for performance evaluation of the proposed technique is carried out to verify various qualities under different partial shading conditions, such as flexibility, reliability, system-independence and high accuracy in tracking the GMPP under non-uniform insolations.