Starfish Optimization-Based Fractional Order 3DoF Control Strategy for Enhanced Frequency Stability in RES-Based Microgrids

Frequency stability in microgrids presents vital challenges owing to unpredictable load variations and intermittent Renewable Energy Sources (RESs). This study investigates enhanced Load Frequency Control methodologies to address stability challenges from unpredictable loads and intermittent renewable energy integration in microgrids. A three degree of freedom fractional order Tilted Integral Derivative Filter Cascaded One Plus Fractional Order Tilted Derivative Accelerator 3DoF-FOTIDN-(1 + FOTDA^γ ) controller is tailored to stabilize frequency in microgrids integrating Photovoltaics (PVs), Wind Turbines (WTs), Fuel Cells (FCs), Electric Vehicles (EVs), Flywheel Energy Storage Source (FESS), Diesel Energy Generator (DEGs), Heat Pumps (HPs), and Controlled Redox Flow Batteries (CRFBs). Lyrebird Optimization Algorithm (LOA) and Walrus Optimization Algorithm (WOA) algorithms, and recently introduced Starfish Optimization Algorithm (SFOA) are employed to optimize controller’s parameters. The Simulation outcomes reveal that the proposed controller with SFOA outperformed three Degree of FreedomProportional Integral Derivative (3DoF-PID), Fractional Order Tilted Integral Derivative Double Derivative squared (FOTIDD² ), and Interval Type-II Fuzzy Fractional Order Proportional Derivative-Proportional Integral (IT2FFOPD-PI). The proposed strategy significantly minimized frequency excursion, fast settling, Overshoot (OSH), Undershoot (USH), and performance indices. The OSH is reduced by 99.77%, USH by 93.07%, Integral Absolute Error (IAE) by 99.20%, Integral Time-weighted Absolute Error (ITAE) by 98.96%, and Integral Squared Error (ISE) by 87.70%, with a settling time of 0.01345 s. Furthermore, the controller is less sensitive to ±40% parametric variations of the generator’s time constant (T_G) with 8.43×10⁻⁶ pu OSH and −7.892×10⁻⁴pu USH respectively. The integration of CRFBs further enhances system stability and resilience under dynamic and uncertain operating conditions.