Performance Enhancement of Boost Converter for Solar Panels System using Genetic Algorithm

Abstract

Solar Panels System (SPS) is a renewable power source with an essential drawback of low output voltage due to the effect of aspects like the intensity of light and ambient temperature. The DC-DC boost converters are significantly used to boost up the SPS voltage under a certain set of conditions. The converter's output voltage and current are unstable, complex, and varied. A three-term controller (proportional, integral, and derivative) is often used because it can control the system’s behavior effectively. The challenge is the selection of the optimum gain parameters of the controller. In this paper, the optimum gain parameters of the controller are selected based on Genetic Algorithm (GA) for the boost converter of SPS. The best operation function of GA based on the tournament, uniform, and constraint dependent is selected by testing and evaluating various genetic algorithm operators, while the objective function based on Integral Time Absolute Error (ITAE) is used to minimize the fitness function. MATLAB code and GA optimization solver are used for simulation results. The simulated results prove the effectiveness of the proposed approach to stabilize and control the boost converter system due to the best specifications of the system. The proposed system enhances the transient response by about (40%) which leads to an increase in the efficiency of the system.