Malicious Corruption-Resilient Wide-Area Oscillation Monitoring Using Principal Component Pursuit
Malicious Corruption-Resilient Wide-Area Oscillation Monitoring Using Principal Component Pursuit
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DOI：
10.1109/tsg.2017.2778054
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发表时间：
2019-03
影响因子：
9.6
通讯作者：
Kaveri Mahapatra;N. Chaudhuri
中科院分区：
文献类型：
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作者：
Kaveri Mahapatra;N. Chaudhuri
提出了一种基于主元追踪（PCP）的同步相量原始数据与广域监测算法之间的接口，以抵御恶意数据破坏。PCP方法为基础的预处理器恢复低秩矩阵的数据矩阵，尽管粗稀疏错误源于网络攻击通过求解凸规划。低秩矩阵由从系统响应获得的基向量组成，稀疏矩阵表示数据矩阵的每个位置的损坏。一个增广拉格朗日乘子为基础的算法来解决PCP问题。求解PCP后得到的低秩矩阵代表重构数据，可用于弱阻尼模态的估计。递归振荡监测算法进行了测试，以验证所提出的方法在环境和瞬态条件下的有效性。
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.