Design of a hybrid fuzzy classifier system for power system sensor status evaluation

Kang Lin, Keith Holbert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Correct estimation of the system operating states in the presence of uncertain measurement data is a crucial challenge for real-time power system monitoring. Proposed in this paper is a strategy that augments state estimation methods using an approach that can incorporate additional information that is not traditionally included as a part of the state variables. Specifically, fuzzy logic is utilized to create a hybrid fuzzy classifier system (HFCS). The HFCS aims to combine information from multiple domains in order to detect, isolate, identify, and mitigate threats to the power networks. Results from applying this HFCS to the IEEE 14-bus test system are presented.

Original languageEnglish (US)
Title of host publication2005 IEEE Power Engineering Society General Meeting
Pages1351-1358
Number of pages8
StatePublished - Oct 31 2005
Event2005 IEEE Power Engineering Society General Meeting - San Francisco, CA, United States
Duration: Jun 12 2005Jun 16 2005

Publication series

Name2005 IEEE Power Engineering Society General Meeting
Volume2

Other

Other2005 IEEE Power Engineering Society General Meeting
CountryUnited States
CitySan Francisco, CA
Period6/12/056/16/05

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Keywords

  • First principle methods
  • Fuzzy logic
  • Neural networks
  • Pattern recognition
  • State estimation

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Lin, K., & Holbert, K. (2005). Design of a hybrid fuzzy classifier system for power system sensor status evaluation. In 2005 IEEE Power Engineering Society General Meeting (pp. 1351-1358). (2005 IEEE Power Engineering Society General Meeting; Vol. 2).