Improved Grey Wolf Optimizer (I-GWO) Based Optimization of PI Controllers for Power Flow in PV-Battery Microgrid Inverters

Abstract

This work introduces an advanced control method for microgrid systems, which includes the use of independent DC/AC converters to link photovoltaic system and battery energy storage system. The research project focuses on enhancing proportional-integrator (PI) controllers, which manage power, voltage, and current levels. The Improved Grey Wolf Optimizer (I-GWO) functions as a metaheuristic algorithm to optimize controller gains, which decreases control errors while improving the system dynamics. The analysis of performance under solar irradiation changes uses MATLAB and Simulink tools to simulate real-world operating scenarios. The optimized controllers receive evaluation against traditional PI controllers through performance metrics that include settling time, overshoot, and the Integral of Time-weighted Absolute Error (ITAE). The I-GWO-tuned controllers demonstrate better performance through reduced overshoot, shorter settling time, and enhanced tracking accuracy. The study demonstrates how metaheuristic optimization techniques enhance the performance of smart microgrids through better power distribution and voltage control, stable energy management, and improved dynamic responses.