Modeling, Analysis, Resilience Improvement of Autonomous AC Microgrids With Virtual Output Impedance Control Under False Data Injection Attacks

This paper focuses on the modeling, analysis, and mitigation of a new false data injection attack targeting the virtual output impedance control of droop-based distributed energy resources in a microgrid with distribution lines of low X/R ratios. It is shown for the first time that the virtual output impedance-targeted false data injection attack is capable of destabilizing the autonomous microgrid, especially when the distribution lines' X/R ratio is sufficiently low. Through small-signal modeling, the low-frequency oscillations and stability margin are comprehensively characterized, providing a theoretical basis for designing resilience-enhancing virtual output impedance controls against false data injection attacks. This method can provide additional damping to microgrids with any low X/R ratio, ensuring an adequate stability margin. To simplify the small-signal model for design analysis, the work adopted the assumptions of light and high-power factor loads, as well as small voltage-angle variations across the microgrid network. A design guideline that considers the damping ratio and the diminishing-return nature of the stabilizing effect provided by the virtual inductance has been developed. The proposed modeling, attack analysis, and resilience-enhancing techniques are comprehensively demonstrated and validated on a two-distributed energy resource microgrid through simulations and experiments. It is shown that the enhanced virtual output impedance control successfully improves the resilience of the microgrid against false data injection attacks, suppressing low-frequency oscillations and maintaining grid stability.