The development of cyber-physical power systems raises concerns about the data quality issue of phasor measurement units (PMUs). Low signal-to-noise ratios (SNRs) and data losses caused by malicious electromagnetic interference, false data injections, and equipment malfunctioning may jeopardize the data integrity and availability necessary for power system monitoring, protection, and control. To ensure grid resiliency, this paper proposes a robust fast PMU measurement recovery (RFMR) algorithm based on improved singular spectrum analysis (SSA) of Hankel structures. It utilizes single or multiple channels of PMU time-series to restore the problematic phasor measurements with low-SNR noises and data losses. Additionally, the traditional singular value decomposition (SVD) and Tucker decomposition (TD) in RFMR are replaced by randomized SVD (RSVD) and sequential TD (STD) to reduce the computational complexity in single-channel and multi-channel RFMR, respectively. Numerical case studies demonstrate that the proposed algorithm can recover the noise-contaminated measurements with higher accuracy than existing methods, such as matrix/tensor decomposition approaches and robust principal component analysis (RPCA), and effectively complement the missing data with the observed measurements corrupted by low SNRs. Moreover, the latency margins of various power system synchrophasor application scenarios can be satisfied with the reduced computational complexity.

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Extensive adoption of Information and Communication Technologies makes power systems and communication systems more tightly coupled to form cyber-physical power systems. It causes power systems to be growingly susceptible to cyber contingencies. Cyber contingencies may sabotage measurement availability, further disrupt the observability analysis in state estimation, and thus threaten the stable operation of power systems. This paper investigates the impact of cyber contingencies on measurement availability. A workflow is presented to achieve accurate and meticulous impact identification under intricate communication architectures with various cyber contingencies. And a set of indicators are proposed to quantitatively evaluate measurement availability. Case studies demonstrate that the proposed method is effective in identifying and assessing the impact of cyber contingencies on measurement availability. Meanwhile, the proposed workflow and indicators can also be employed to dynamically evaluate the system's resilience in protecting measurement transmission against hypothetical cyber contingencies, which could benefit the offline planning and online operation of cyber-physical power systems 1This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.