Fast event identification through subspace characterization of PMU data in power systems
This paper proposes a data-driven fast 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. A dictionary of subspaces that correspond to different events are established off-line, and an event is identified online with the most similar subspace in the dictionary. Both theoretical and numerical analysis demonstrate that the subspace of PMU data is characteristic of system events and is robust to system initial conditions. This compact representation reduces the dictionary size and the computational time of the event identification method. The proposed method is evaluated numerically on simulated events in an IEEE 68-bus power systems.