Wavelet Ridge Technique Based Analysis of Power System Dynamics Using Measurement Data

Abstract

In this paper, a wavelet ridge technique based approach is applied to analyze wide area measurement systems data representing power system dynamic behavior. When used to extract the oscillating trend from the measured network frequency signal, it efficiently tracks the oscillations in the presence of significant noise. Using multivariate signal analysis, a novel disturbance contribution index for individual generator is proposed to estimate how much a generator's contribution is in a severely disturbed power system, as recorded by various phasor measurement units. In other words, this index helps in quantifying how severely affected a particular machine is following a system-wide disturbance. It is shown that any control action applied on the most disturbed generator as identified by the disturbance contribution index, stabilizes the overall system more quickly, compared to the cases where control action is applied on other generators. When the analytic wavelet is used to extract the dynamic pattern from the signal, the recovered signal is also analytic. A new coherency index is also proposed, based on the properties of analytic signal, to indicate how similar two measured signals are. The proposed technique is demonstrated using synthetic signals, signals obtained from time-domain simulation of various power systems and actual phasor measurement units data.