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Modern cyber-physical microgrids rely on the information exchanged among power electronics devices (i.e., converters or inverters with local embedded controllers) making them vulnerable to cyber manipulations. The physical devices themselves are susceptible to potential faults and failures. Effects of these cyber and physical anomalies can propagate throughout the entire microgrid due to information exchanged and the inherent low inertia of the distribution network. This work employs the parametric time-frequency logic (PTFL) framework to detect such cyber-physical anomalies. PTFL is a formalism to analyze the time-frequency content of the observable quantities of interest (such as current, voltage, or frequency) of power electronics devices in comparison with the predefined time-frequency properties. PTFL formalism is presented to detect the anomalies such as false data-injection attacks, denial-of-service attacks, and faults on a cluster of four DC microgrids and an inverter-populated IEEE 34-bus feeder system in a controller/hardware-in-the-loop environment.

Cyber-Physical Anomaly Detection in Microgrids Using Time-Frequency Logic Formalism