A Novel ZSV-Based Detection Scheme for FDIAs in Multiphase Power Distribution Systems

Chengran Ma,Hao Liang,Yindi Jing

IEEE Transactions on Smart Grid(2023)

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摘要
Modern power systems are vulnerable to false data injection attacks (FDIAs) due to the widespread applications of two-way communication networks for system operation and control. Diagnosing such malicious attacks are of great significance for the resilient operations of power systems. Yet, in literature, the majority of studies in FDIA detection focus on power transmission systems. In this paper, a novel FDIA detection scheme is proposed for three-phase distribution systems based on zero-sequence voltage (ZSV). From the voltage and power measurements, the bus voltages are estimated, and then the estimated ZSV is calculated as the sum of the estimated bus voltages on the three phases to represent the degree of unbalance of the distribution system. Via mathematical analysis of the linear distribution system state estimation (DSSE) model, the distribution of the estimated ZSV under the normal condition is derived, based on which a whitening process is adopted on the estimated ZSV to weaken the effect of measurement noises. The $\mathcal {L}_{2}$ -norm of the whitened ZSV vector is then compared with a predefined threshold for FDIA detection. Moreover, the probability of false alarm of the proposed scheme is derived, which can be utilized to determine the detection threshold for a desired tolerance of false alarm rate. The proposed scheme is validated on several IEEE Test Feeders and simulation results show the effectiveness of the proposed scheme in detecting FDIAs in three-phase distribution systems.
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关键词
Anomaly detection,distribution systems,false data injection attacks,state estimation,zero-sequence voltage
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