A hybrid global maximum Power Point tracker for photovoltaic systems under complex partial shading conditions

Abstract

In Photovoltaic (PV) systems, maximum power point tracking (MPPT) is an indispensable task. To date, various MPPT techniques have been proposed in the literature using different methods. In this work, we performed initially a comprehensive comparative study of the most adopted MPPT techniques. Thereafter, we proposed a hybrid maximum power point tracker (MPPT) for photovoltaic (PV) system under complex partial shading conditions. The proposed algorithm combines conventional techniques with meta-heuristic algorithm i.e., the particle swarm optimization (PSO). By doing so, a fast, accurate and reliable tracking of the global maximum power point (GMPP) is guaranteed. The search space is fully scrutinized such that the convergence to GMPP is guaranteed. The performance of the proposed technique is evaluated against highly competitive MPPT algorithms. Tests are made to verify the correctness tracking of the GMPP under complex partial shading conditions. For experimental verification, hardware based photovoltaic array simulator is used in conjunction with a buck-boost converter. The proposed algorithm was implemented using the TMS320F240 DSP of dSPACE DS1104 board.