A Hybrid GWO-MPO-Based Maximum Power Point Tracking for Photovoltaic System for a New MLI with Minimum Number of Switches

Hussein S. Abdulazeez, Rabee’ H. Thejel, Diyah K. Shary


Photovoltaic (PV) systems provide a number of challenges, one of the most critical of which is determining how to extract the maximum amount of usable power from the PV system even when the system is running in conditions of fast change in irradiance. This study aims to demonstrate a novel hybrid approach to maximum power point tracking (MPPT), which is built on the grey wolf optimization algorithm (GWO) and modified perturb and observe (MP&O) techniques. The second goal of this method is to provide a robust MPPT method with minimum losses in the MPP point of the PV module. This technique is based on the connection of a single KC200GT PV module. The KC200GT PV module is connected to the DC bus via DC/DC boost converter to raise the voltage and implement the MPPT algorithm. After that, the PV system was integrated to supply a new multilevel inverter (MLI) with a reduced number of switches. Additionally, the MATLAB/Simulink environment was used to demonstrate and evaluate the efficacy of the proposed MPPT approach. Complex fast changes in solar irradiation are applied to the module to verify the feasibility and efficacy of the hybrid method by comparing its performance to that of the P&O, and MP&O algorithms. The obtained results demonstrated that the hybrid GWO-MP&O MPPT method achieved an excellent level of efficacy in terms of MPP accuracy, convergence speed (0.05 sec), and overall tracking efficiency (99.7%) compared to other approaches.


Keywords: Grey Wolf Optimizer, maximum power point, boost converter, photovoltaic system, multilevel inverter, perturb and observe.



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