designing a multi-objective optimized parallel process controller for frequency stabilization in an islanded microgrid

Load-frequency control plays a critical role in maintaining the stability and reliability of islanded microgrids, where the absence of a large interconnected grid makes frequency regulation more challenging. with the increasing integration of renewable energy sources and energy storage systems, the stochastic and uncertain nature of µgs component's behavior has amplified the need for advanced lfc mechanisms, making it a focal area of research for decades. this paper introduces a novel parallel process fopi–fpod controller optimized for robust lfc and stability in µgs. employing time and frequency domain objective costs, a multi-objective particle swarm optimization algorithm with nonlinear time-varying coefficients generates a pareto front, with fuzzy decision-making selecting optimal designs. the proposed controller demonstrates strong robustness by effectively handling uncertainties such as sudden load changes, res fluctuations, and parametric variations, while maintaining stable frequency regulation. the controller's performance is evaluated under four scenarios: sudden load changes with time delays, uncertainties in ress, parametric system uncertainties, and energy storage systems' impact. comparative analysis with pid, fopid, and pd(1+pi) controllers demonstrates the proposed design's superior stability and resilience, providing a robust solution for frequency stabilization in µgs. numerical results demonstrate that the proposed fopi–fopd controller significantly outperforms traditional methods, achieving lower error indices, reduced frequency deviations, and more efficient utilization of energy storage systems under various scenarios and energy storage systems participation levels. these findings highlight its robust and adaptive performance in ensuring stable and efficient lfc task for an islanded µgs control.