Walrus Optimization-Based Adaptive Virtual Inertia Control for Frequency Regulation in Islanded Microgrids

Microgrids with high renewable energy penetration face critical challenges in frequency stability due to reduced system inertia and the presence of parameter uncertainties. This study introduces a novel adaptive virtual inertia control strategy utilizing a combination of the Walrus Optimization Algorithm (WaOA), a recent metaheuristic optimization technique, and Proportional–Integral–Derivative (PID) controllers (WaOA-PID) to improve frequency regulation in islanded microgrids under diverse operating conditions. The proposed method is evaluated across three scenarios: medium inertia, low inertia, and parametric uncertainty. Comparative analyses with conventional, IMC-tuned PID and H∞ Vector Internal Controllers (VIC) reveal that the WaOA-PID controller achieves the lowest overshoot, undershoot, and rate of change of frequency (RoCoF), while maintaining acceptable settling times in all cases. At an estimated load deviation of 0.18, the demand is varied from 200 MW to 250 MW to evaluate the system’s performance. The proposed technique yields an Integral Time Absolute Error (ITAE) of 0.000576, with PID gains of Ki = 0.9994, Kd = 0.185, and Kp = 0.774. Compared to traditional methods, the proposed controller demonstrates high reliability and efficiency in maintaining load frequency control and enhancing power system management, validating its suitability for real-time renewable energy-integrated microgrid applications.