A new method for classification and characterization of voltage sags

Mladen Kezunovic, Yuan Liao

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


This paper presents new software developments related to sag classification and characterization. A new fuzzy rule based algorithm for classifying the types of voltage sags is proposed. The voltage sags are categorized into three types, i.e. sags due to the faults, large motor starting, or due to interaction between motor operation and faults. Three distinctive features of sag waveforms are defined and extracted first. Then a fuzzy logic based inference engine utilizing these features as inputs is implemented for decision making. Also presented are the characterization methods and suggested monitoring parameters for each of the three types of sags. Finally the application of the proposed characterization approaches for the equipment sensitivity study is illustrated. The results of case studies are reported. The presented approach has been implemented in MATLAB.

Original languageEnglish
Pages (from-to)27-35
Number of pages9
JournalElectric Power Systems Research
Issue number1
StatePublished - May 21 2001

Bibliographical note

Funding Information:
The developments reported in this paper are funded by the Texas Higher Education Coordinating Board Advanced Technology Program. The co-funding is provided by TXU Electric and Gas and Reliant Energy HL&P.


  • Fuzzy logic
  • Parameter estimation
  • Pattern classification
  • Power quality
  • Voltage sag

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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