With oil fields expressing an increasing need for dependable and renewably powered systems, considerable attention is being directed towards hybrid renewably integrated grid-connected microgrids. This work implements the assimilation of the Hawkfish Optimization Algorithm coupled with fuzzy logic for a hybrid microgrid metaheuristic approach to control frequency stabilization. This research focuses on a hybrid unit which consists of wind turbines, solar photovoltaics, and conventional fuel subsystems. This approach deals explicitly with the intrinsic instability of the intermittent renewable resources as they pose serious challenges to the frequency stability of the microgrid. For the proposed method, the hybrid system is first modeled, followed by system design of three control schemes which include classical PI, fuzzy PI, and an HFOA-optimized fuzzy PI control scheme. Simulation results demonstrate the dominance of HFOA-optimized fuzzy control in terms of system dynamic response control, parameter variation and load disturbance disturbance robustness, and in control of disturbance rejection among the three. Additionally, to complete the proposed control architecture on the control hierarchy, a set of Distributed Energy Resources (DERs) which include Fuel Cells, Battery Energy Storage Systems (BESS), and Flywheel Energy Storage Systems (FESS) is controlled on different subsystems of control hierarchy. The application of intelligent control methods, particularly the combination of fuzzy logic and HFOA, enhances the reliability, competence, and frequency control of advanced microgrid systems. This research advances the implementation of intelligent control methods in renewable energy dominant microgrids and aids the transition towards more intelligent resilient power systems.