Power quality disturbance classification utilizing S-transform and binary feature matrix method

Thai Nguyen, Yuan Liao

Research output: Contribution to journalArticlepeer-review

85 Scopus citations

Abstract

This paper presents new features and a novel decision-making system for automated classification of power quality disturbances. The most common types of disturbances including flickers, harmonics, impulses, notches, outages, sags, swells, and switching transients are studied. Disturbances consisting of both sag and harmonic, or both swell and harmonic are also considered. It is assumed that the analyzed waveforms are available in sampled form. The signal processing techniques utilized to extract the distinctive features of the waveforms are Fourier and S-transform. A new method based on binary feature matrix is designed for making a decision regarding the disturbance type. Evaluation studies for verifying the accuracy of the method are presented.

Original languageEnglish
Pages (from-to)569-575
Number of pages7
JournalElectric Power Systems Research
Volume79
Issue number4
DOIs
StatePublished - Apr 2009

Keywords

  • Binary feature matrix
  • Power quality disturbance classification
  • S-transform

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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