A comparison of global MPPT techniques for partially shaded grid-connected photovoltaic system

Abstract

Maximizing the energy reproduced from a solar power generation system becomes a challenging task when high changes in irradiation or Partial Shading (PS) are experienced. The latter case is considered as one of the unavoidable complicated phenomena since the Photovoltaic (PV) system is extremely affected by displaying numerous local maxima. Thus, it is compulsory to rigorously choose an accurate Maximum Power Point Tracking (MPPT) which identifies effectively the unique Global Point (GP) and avoid any local peaks with the purpose of mitigating the impact of PS. Conventional methods are prone to failure in case of an unpredictable shadow. This paper introduces a comparative assessment of Particle Swarm Optimization (PSO) based MPPT, Genetic Algorithm (GA) based MPPT and P&O for a partially shaded grid-connected photovoltaic system. The main contribution of the paper consists in developing a new variant of PSO algorithm which is a good tradeoff between simplicity, speed, and efficiency. The grid side control is investigated as well through developing different control loops with PID controllers tuned by GA. Various schemes of irradiation and PS are used in order to verify the ability of the threefold algorithms to adequately track the GP.