This paper presents a novel Metaheuristic-Driven Hawkfish Fuzzy Logic Control (HFFLC) framework for frequency stabilization in grid-connected microgrids with high renewable energy penetration. The proposed system integrates a fuzzy logic controller with the Hawkfish Optimization Algorithm (HFOA)—a bio-inspired metaheuristic that dynamically tunes fuzzy membership functions, rule weights, and scaling factors to ensure optimal performance under varying operating conditions. The microgrid model incorporates photovoltaic (PV) arrays, wind turbines, fuel cells, and energy storage units (battery and flywheel), coordinated through smart inverters and converters. Simulation results demonstrate that the proposed HFFLC achieves significantly improved transient and steady-state performance compared to conventional controllers and previously reported methods. Specifically, the system attained a settling time of 1.6 s, overshoot of 2.0%, frequency deviation RMSE of 0.006 Hz, and Total Harmonic Distortion (THD) of 2.6%, outperforming benchmark methods by S. M (2020), Marhraoui et al. (2022), Ranjbar and Hosseini (2019), and Sheshyekani et al. (2019). The results confirm that the hybridization of fuzzy reasoning and hawkfish-inspired optimization enhances dynamic response, stability, and control precision in microgrid operation. Overall, the proposed approach provides a robust and computationally efficient solution for intelligent frequency regulation and energy management in smart grid applications.