Robust Detection and Analysis of Power System Oscillations Using the Teager-Kaiser Energy Operator

Abstract

Critical to real-time oscillations monitoring is early detection when otherwise dormant natural modes become a serious threat to grid stability. The next urgent issue is to determine the frequency and damping of the problematic modes when the signal is embedded in noise and the system contains closely spaced natural modes. The present paper addresses the detection issue using the Teager-Kaiser energy operator (TKEO) which has shown to be a fast predictor of the instability onset time when applied to the output signals of an orthogonal filter bank. In the system stability context, linear filter decomposition (LFD) is preferred rather than empirical mode decomposition (EMD), well known for its tendency to generate artificial modes with no physical meaning. A narrowband LFD with a less than 0.2-Hz bandwidth is achieved in the range 0.05 to 3 Hz through a cosine-modulated filter bank design. The effectiveness of the scheme in accurately detecting and tracking the frequency and damping of oscillatory modes is demonstrated using Monte Carlo simulations of three closely spaced modes and a detailed analysis of an actual event recorded by Hydro-Québec's WAMS in 2006.