Metaheuristic Optimization of MPC Parameters for Power Quality Improvement in PV–Battery Microgrids

Ch. Jgnana Sree1, Sri M. Sunil Kumar2 Assistant Professor

1 Electrical and Electronics Engineering, Sir C. R. Reddy College of Engineering(A), Eluru.

2 Electrical and Electronics Engineering, Sir C. R. Reddy College of Engineering(A), Eluru.

Abstract - The integration of photovoltaic (PV) systems into modern power networks introduces challenges related to voltage fluctuations, harmonic distortion, and power quality degradation. This paper presents a Marine Predators Algorithm (MPA)-optimized Model Predictive Control (MPC) approach for improving the performance of a grid-connected PV–battery microgrid system. The proposed system consists of a photovoltaic array, boost converter, battery energy storage system, and three-level voltage source inverter developed in MATLAB/Simulink environment. A Genetic Algorithm (GA)-based Maximum Power Point Tracking (MPPT) method is used to enhance power extraction from the PV array. The Marine Predators Algorithm is applied to optimize important MPC parameters for improving voltage regulation and dynamic response. Simulation results demonstrate improved system stability, reduced harmonic distortion, and enhanced power quality compared to conventional control methods. The proposed optimization-based predictive control strategy provides an efficient solution for renewable energy applications.

Key Words:  Photovoltaic System, Model Predictive Control (MPC), Marine Predators Algorithm (MPA), Power Quality Improvement, Voltage Source Converter (VSC), Maximum Power Point Tracking (MPPT), Renewable Energy Systems.