A Hilbert-Huang based approach for on-line extraction of modal behavior from PMU data

In this paper an efficient method for analyzing the local dynamics of transient oscillations using a local empirical mode decomposition (EMD) and the Hilbert transform is presented. Two novel approaches are investigated to characterize non-stationary issues. The first method is a local implementation of the EMD technique. The second technique is an algorithm to compute the Hilbert transform using variable window filters. By combining a sliding window of finite length with the sifting process by blocks, a local implementation of the empirical mode decomposition is proposed. Approaches to extending Hilbert-Huang analysis to analyze the local properties of general non-stationary signals are then explored based on finite-impulse-response (FIR) designed using Kaiser windows. This approach enables the Hilbert-Huang technique to be a truly online analysis technique for measured data. The application of these techniques is tested on time-synchronized phasor measurements collected by Phasor Measurement Units. Both, online analysis and off-line analysis are used in the study.