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.

中文翻译：

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PMU数据中的恶意腐败复原力和广域阻尼控制

本文提出了相量测量单元（PMU）数据中恶意破坏复原力的框架，以及将其应用于广域阻尼控制的方法。在原始PMU测量中检测损坏的问题被表述为压缩的传感问题，并使用基于lp范数（0 <; p <; 1）的在线鲁棒主成分分析（RPCA）算法来恢复受损信号。使用基于l1范数的RPCA算法，针对不同的破坏模式，比较了所提出方法的性能。在16机5区域新英格兰-纽约系统的闭环广域电力振荡阻尼控制中，证明了使用拟议的数据预处理体系结构纠正因丢失数据攻击而损坏的原始PMU反馈信号的有效性。