Title
Malicious Corruption-Resilient Wide-Area Oscillation Monitoring Using Principal Component Pursuit
Abstract
A principal component pursuit (PCP)-based interface is proposed between raw synchrophasor data and the algorithms used for wide-area monitoring application to provide resilience against malicious data corruption. The PCP method-based preprocessor recovers a low rank matrix from the data matrix despite gross sparse errors originating from cyber-attacks by solving a convex program. The low-rank matrix consists of the basis vectors obtained from the system response and the sparse matrix represents corruption in each position of the data matrix. An augmented Lagrangian multiplier-based algorithm is applied to solve the PCP problem. The low rank matrix obtained after solving PCP represents the reconstructed data and can be used for estimation of poorly damped modes. A recursive oscillation monitoring algorithm is tested to validate the effectiveness of the proposed approach under both ambient and transient conditions.
Year
DOI
Venue
2019
10.1109/TSG.2017.2778054
IEEE Transactions on Smart Grid
Keywords
Field
DocType
Sparse matrices,Phasor measurement units,Monitoring,Matrix decomposition,Oscillators,Principal component analysis,Damping
Data mining,Matrix (mathematics),Matrix decomposition,Preprocessor,Augmented Lagrangian method,Low-rank approximation,Data Corruption,Engineering,Sparse matrix,Principal component analysis
Journal
Volume
Issue
ISSN
10
2
1949-3053
Citations 
PageRank 
References 
1
0.36
0
Authors
2
Name
Order
Citations
PageRank
Kaveri Mahapatra131.42
Nilanjan Ray Chaudhuri2155.52