Power system event classification via dimensionality reduction of synchrophasor data

This paper explores a potential approach to fast classifying power system events using online synchrophasor measurements. The approach is based on dimensionality reduction of the emerging ambient phasor measurement unit (PMU) data. In contrast with model-based analysis, the proposed approach does not require a system model. It projects real-time PMU data onto the core subspace constructed from pre-event data, and then utilizes their scatter plots to detect and classify the system events. Projections lying outside the core subspace indicate the occurrence of an event, and the topological shapes of these projections classify the events. Numerical examples using synthetic PMU data are conducted to demonstrate the efficacy of the proposed approach.