Intelligent data analysis for power systems

Wen Fan, Yuan Liao, Theo Laughner, Bruce Rogers, George Pitts, Joshua L. Wooten, James Rossman, Fred Elmendorf

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


This paper presents potential techniques for automated analysis of various types of data collected in power systems. Diverse recording devices have been widely deployed in modern power systems, and as a result more data have been obtained. It is necessary to extract useful and actionable information from the captured data. This paper focuses on discussing intelligent techniques for automatically analyzing such data, including disturbance classification, fault events correlation, fault type classification, fault cause identification, fault location, generator monitoring and parameter estimation, incipient fault detection, and line parameter estimation.

Original languageEnglish
Title of host publication2012 IEEE Power and Energy Society General Meeting, PES 2012
StatePublished - 2012
Event2012 IEEE Power and Energy Society General Meeting, PES 2012 - San Diego, CA, United States
Duration: Jul 22 2012Jul 26 2012

Publication series

NameIEEE Power and Energy Society General Meeting
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933


Conference2012 IEEE Power and Energy Society General Meeting, PES 2012
Country/TerritoryUnited States
CitySan Diego, CA


  • Disturbance analysis
  • Fault location
  • Power quality
  • Substation automation

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering


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