Nonstationary approaches to trend identification and denoising of measured power system oscillations

Arturo Roman Messina, Vijay Vittal, Gerald Thomas Heydt, Timothy James Browne

Research output: Contribution to journalArticlepeer-review

61 Scopus citations


This paper discusses the application of nonstationary time-frequency analysis techniques to identify nonlinear trends and filtering frequency components of the dynamics of large, interconnected power systems. Two different analytical approaches to examine nonstationary features are investigated. The first method is based on selective empirical mode decomposition (EMD) of the measured data. The second is based on wavelet shrinkage analysis. Experience with the application of these techniques to quantify and extract nonlinear trends and time-varying behavior is discussed and a physical interpretation of the proposed algorithms is provided. The practical application of these techniques is tested on time-synchronized phasor measurements collected by phasor measurement units (PMUs). Numerical simulations computed using time-energy nonstationary methods are critically compared with conventional approaches.

Original languageEnglish (US)
Pages (from-to)1798-1807
Number of pages10
JournalIEEE Transactions on Power Systems
Issue number4
StatePublished - 2009


  • Inter-area oscillations
  • Nonstationarity
  • Power system dynamics
  • Power system oscillations
  • Synchrophasors
  • Time-synchronized phasor measurement systems
  • Wide-area measurements

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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