1 research outputs found
A PMU-based Multivariate Model for Classifying Power System Events
Real-time transient event identification is essential for power system
situational awareness and protection. The increased penetration of Phasor
Measurement Units (PMUs) enhance power system visualization and real time
monitoring and control. However, a malicious false data injection attack on
PMUs can provide wrong data that might prompt the operator to take incorrect
actions which can eventually jeopardize system reliability. In this paper, a
multivariate method based on text mining is applied to detect false data and
identify transient events by analyzing the attributes of each individual PMU
time series and their relationship. It is shown that the proposed approach is
efficient in detecting false data and identifying each transient event
regardless of the system topology and loading condition as well as the coverage
rate and placement of PMUs. The proposed method is tested on IEEE 30-bus system
and the classification results are provided