A fuzzy-expert system for classifying power quality disturbances

Yuan Liao, Jong Beom Lee

Research output: Contribution to journalArticlepeer-review

111 Scopus citations

Abstract

This paper presents a fuzzy-expert system for automated detection and classification of power quality disturbances. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, impulses, flickers, harmonics, and notches. It is assumed that the analyzed waveforms are available in sampled form. Fourier transform and wavelet analysis are utilized to obtain unique features for the waveforms. A fuzzy-expert system is designed for making a decision regarding the type of the disturbance. Simulation studies are presented to verify the accuracy of the proposed approach. Comparison studies between an Artificial Neural Network based classification technique and the proposed approach are also reported to show the advantages of the proposed approach.

Original languageEnglish
Pages (from-to)199-205
Number of pages7
JournalInternational Journal of Electrical Power and Energy System
Volume26
Issue number3
DOIs
StatePublished - Mar 2004

Bibliographical note

Copyright:
Copyright 2008 Elsevier B.V., All rights reserved.

Keywords

  • Artificial neural network
  • Fuzzy-expert system
  • Power quality disturbance classification
  • Wavelet analysis

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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