Frequency Stability Enhancement Using Genetic Algorithm in an Islanded Microgrid System

This research presents an advanced control framework designed to enhance frequency stability in an islanded microgrid (MG) that incorporates various Distributed Energy Resources (DERs) along with energy storage solutions. The setup of the MG features wind turbine generators (WTG), photovoltaic (PV) systems, diesel engine generators (DEG), fuel cells (FC), flywheel energy storage systems (FESS), and Battery energy storage systems (BESS). An aqua electrolyzer is employed to convert surplus renewable energy into hydrogen for fuel cell use, thus creating a hybrid energy cycle. Frequency management is tackled using PD and PID controllers, with the PID controller being improved by the Genetic Evolutionary Optimization (GEO) algorithm. Simulations are conducted in MATLAB/Simulink under dynamic load conditions to assess the system's performance. The findings indicate that the GEOoptimized PID controller significantly improves frequency response, demonstrating reduced deviation, quicker settling times, and enhanced steady-state accuracy compared to traditional controllers that were adjusted using trial-and-error methods. These outcomes highlight that intelligent optimization techniques can strengthen the resilience and adaptability of control systems for microgrids that integrate renewable energy resources.