Adaptive Virtual Inertia Strategies for Frequency Stability in Low Inertia Power Networks using Fuzzy logic controller

This paper presents an adaptive virtual inertia control strategy based on a fuzzy logic controller (FLC) for improving frequency stability in low-inertia power systems with high penetration of inverter-based renewable energy sources. As conventional synchronous generators are replaced by converter-interfaced units, system inertia decreases, leading to faster and deeper frequency deviations during disturbances. The proposed controller emulates the inertial response of traditional machines while dynamically adjusting virtual inertia and damping parameters according to real-time frequency deviations and rate of change of frequency (RoCoF). The fuzzy logic system enables intelligent decision-making under nonlinear and uncertain operating conditions, enhancing flexibility and robustness. The model is implemented in MATLAB R2023a, where system performance is evaluated under various disturbance scenarios. Simulation results show significant improvements in transient stability, including reduced frequency nadir, overshoot, and RoCoF, alongside faster settling times. Compared to conventional fixed-inertia methods, the proposed adaptive approach demonstrates superior resilience and smoother dynamic recovery, confirming its effectiveness in maintaining stable operation in renewable-dominated power networks. This study provides a practical and scalable framework for enhancing frequency regulation and reliability in future smart grids.