Improving the performance of grid connected PV system with dynamic voltage restorer using geometric mean optimization

Abstract This paper presents a grid-connected photovoltaic (PV) system integrated with a Dynamic Voltage Restorer (DVR) to mitigate power quality issues caused by PV penetration into the grid. The increasing integration of PV into power networks introduces challenges such as voltage fluctuations, harmonic distortions, and reduced efficiency, potentially leading to grid instability. To address these issues, a DVR optimized using the Geometric Mean Optimization (GMO) technique is implemented for enhanced power quality and voltage regulation. The proposed GMO-based tuning of the Proportional-Integral (PI) controller achieves optimal gains of kp = 12.09, ki = 14.97, with a best fitness value of 0.00198 and a standard deviation of 0.0024, ensuring precise and stable control. Furthermore, a Crayfish Optimization Algorithm (COA)-based Maximum Power Point Tracking (MPPT) method is employed to enhance power extraction from the PV system under varying irradiation conditions. With COA MPPT, the PV system achieves an efficiency of 99.9%, delivering a peak power output of 5.802 kW. Simulation results in MATLAB/Simulink validate the effectiveness of the proposed control strategy, demonstrating enhanced power quality, improved system efficiency, and stable grid operation. The combination of COA-based MPPT and GMO-optimized DVR ensures optimal performance of the grid-connected PV system, making it a reliable solution for mitigating power quality issues in modern power grids.