Abstract

This paper proposes a dynamic maximum power point tracking (MPPT) controller for a solar photovoltaic (SPV) system with a battery charging circuit. The voltage and current, and consequently the maximum available power of SPV panels vary based on environmental conditions. To operate SPV system at maximum power point under different weather conditions, a cascaded (PI-PD) controller with PSO gain scheduling is suggested in this paper. Also, the FOPI control is applied to an accurate dynamic model of the buck converter to function as a charge controller. For tuning the FOPI controller parameters, a stochastic inertia weight GWO algorithm is employed which maintains an appropriate balance between detection and hunting strategies, and gives the fittest wolf position during iterations. The proposed algorithm is compared with the original GWO algorithm to show its superiority. The accuracy of the proposed cascaded controller used in the SPV system to find MPP ranges from 96.05% to 98.87%. The goal of this study is to operate the SPV panel at maximum power point under variable atmospheric conditions to increase efficiency at a lower cost. It also provides appropriate current and voltage for faster battery charging, thereby increasing the life span of the battery. The system is implemented and analyzed in MATLAB/Simulink, and results are validated.

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