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Hilbert spectral analysis (HSA) is used to characterize the time evolution of non-stationary power system oscillations following large perturbations. Using an analytical procedure based on the Hilbert-Huang Technique (HHT), data from transient stability simulations are decomposed into a finite number of time-varying oscillating components that can be associated with different time scales. Hilbert analysis is then utilized to characterize the time evolution of critical components giving rise to the observed oscillations. The objectives of this study are to obtain information of a quantitative nature on nonlinear processes in power system oscillatory phenomena and assess the applicability of the developed procedures to track the evolving dynamics of critical system modes. A six-area, 377-machine power system is analyzed to examine the onset of nonlinear, non-stationary behavior. Examples of the developed procedures to detect and quantify the strength of nonlinear interaction in power system behavior and to estimate the distribution of the non-stationarity are provided
Messina et al. (2006) studied this question.