Pmu Change Point Detection Of Imminent Voltage Collapse And Stealthy Attacks

Phasor Measurement Units (PMUs) provide significant value towards ensuring autonomous cognition in the power grid by enabling the abnormal events to be fault-detected and so as to trigger proactive measures to avoid large catastrophic system states. For instance, a change in the baseline distribution of PMU signals can indicate imminent voltage collapse, false data injection, and other security threats. Fractal geometry inspired analysis of PMU signals (via the Hurst exponent) reveals that an imminent voltage collapse is preceded by a significant increase in the Hurst exponent. We propose a novel change point detection strategy that optimally anticipates the fractal geometry change point from the PMU signals subject to a pre-specified false alarm rate.