LAUSR

Abstract Wide-area power system monitoring based on phasor measurement units allows collecting a set of physical variables for evaluating the system security and stability, as well as for detecting power system disturbances. However, trends, noise and non-Gaussian distribution in measurements are important challenges for carrying out the detection, localization and visualization of power system disturbances. In this paper, a methodology that combines independent component analysis with statistical indices for detecting and visualizing anomalous dynamic events from wide-area measurements is proposed. From the statistical indices, two charts are also proposed to provide a better understanding of the system disturbances. Finally, a set of simulated data obtained from a transient stability model of the New England/New York test system is used to demonstrate the effectiveness of the proposed technique.