Data clustering and storing for wide-area power quality monitoring

A. M. Gaouda

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This paper presents a new technique that can be implemented for monitoring the quality of serves in wide areas and representing the data in terms of a small set of coefficients. Wavelet multi-resolution analysis (MRA) is utilized for feature extraction and data clustering of different disturbances. The proposed feature vector and the rapid drop off in the number of the wavelet-expansion coefficients are used to classify different power quality problems and to represent the original data in terms of a small set of coefficients.

Original languageEnglish
Pages (from-to)56-63
Number of pages8
JournalElectric Power Systems Research
Volume70
Issue number1
DOIs
Publication statusPublished - Jun 2004

Keywords

  • Data representation
  • Multi-resolution signal decomposition
  • Power quality
  • Wavelet analysis

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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