A Hybrid Global Maximum Power Point Tracking Technique With Fast Convergence Speed for Partial-Shaded PV Systems

Abstract

Photovoltaic (PV) systems exhibit multiple local and one global maximum power points (MPPs) in their P – V and I – V curves during partial shading conditions (PSC). Thus, to improve the efficiency of the system, a global maximum power point tracking (GMPPT) algorithm is necessary. This paper presents a hybrid GMPPT algorithm for constant voltage load applications using a single current sensor. The proposed method combines single current sensor hill climbing (SSHC) and artificial bee colony (ABC) algorithms to track the GMPP. The SSHC algorithm detects the event of PSC and tracks the MPP during uniform insolation conditions. The output current of the power electronic interface is measured effectively at selective duty cycles to identify the type of P – V curve pattern and, thus, initiate either SSHC or ABC. The search space for the ABC algorithm is reduced in the proposed technique to improve the convergence speed. The proposed GMPPT technique is simulated in MATLAB and validated through experimental prototypes for various PSCs. The proposed algorithm tracks the GMPP with excellent efficiency and fast speed.