Real-Time Event Identification Through Low-Dimensional Subspace Characterization of High-Dimensional Synchrophasor Data

This paper proposes a data-driven real-time event identification method based on the measurements of Phasor Measurement Units (PMUs). The central idea is to characterize an event by the low-dimensional subspace spanned by the dominant singular vectors of a data matrix that contains spatial-temporal blocks of PMU data. The subspace representation is robust to system initial conditions and characterizes the system dynamics. A dictionary of subspaces that correspond to different events are established offline, and an event is identified online with the most similar event in the dictionary through subspace comparison. The compact subspace representation reduces the dictionary size and the computational time of the event identification method. Numerical experiments on both simulated events in an IEEE 68-bus power system and the recorded data in New England validate the proposed method.