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

Kaveri Mahapatra; Mahmoud Ashour; Nilanjan Ray Chaudhuri; Constantino M. Lagoa

doi:10.1109/TSG.2019.2928340

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

Kaveri Mahapatra, Mahmoud Ashour, Nilanjan Ray Chaudhuri, Constantino M. Lagoa

Research output: Contribution to journal › Article › peer-review

24 Scopus citations

Abstract

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.

Original language	English (US)
Article number	8760545
Pages (from-to)	958-967
Number of pages	10
Journal	IEEE Transactions on Smart Grid
Volume	11
Issue number	2
DOIs	https://doi.org/10.1109/TSG.2019.2928340
State	Published - Mar 2020

All Science Journal Classification (ASJC) codes

General Computer Science

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title = "Malicious Corruption Resilience in PMU Data and Wide-Area Damping Control",

abstract = "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.",

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AB - 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.

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

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