Malicious Corruption Resilience in PMU Data and Wide-Area Damping Control

This paper presents a framework for malicious corruption resilience in phasor measurement unit (PMU) data and a methodology for applying this in wide-area damping control. The problem of detecting corruptions in raw PMU measurements is formulated as a compressed sensing problem and the compromised signals are recovered using an lp -norm (0 < p < 1)-based online robust principal component analysis (RPCA) algorithm. The performance of the proposed method has been compared for different patterns of corruption with an l1-norm-based RPCA algorithm. The effectiveness of using the proposed data preprocessing architecture for correcting raw PMU feedback signals corrupted by missing data attack was demonstrated for closed-loop wide-area power oscillation damping control in 16-machine, 5-area New England-New York system.