Reducing state estimation uncertainty through fuzzy logic evaluation of power system measurements

Keith Holbert, Kang Lin

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

6 Scopus citations

Abstract

State estimation is widely used for bad data detection and identification. To further insure the validity of measurements from the power system, additional information is incorporated into sensor fault detection and isolation schemes. In particular, we develop a fuzzy logic-based state estimation method that includes data such as historical usage trends and component reliability. Results from applying this hybrid fuzzy classifier system to the IEEE 14-bus test system are presented.

Original languageEnglish (US)
Title of host publication2004 International Conference on Probabilistic Methods Applied to Power Systems
Pages205-211
Number of pages7
StatePublished - Dec 1 2004
Event2004 International Conference on Probabilistic Methods Applied to Power Systems - Ames, IA, United States
Duration: Sep 12 2004Sep 16 2004

Publication series

Name2004 International Conference on Probabilistic Methods Applied to Power Systems

Other

Other2004 International Conference on Probabilistic Methods Applied to Power Systems
CountryUnited States
CityAmes, IA
Period9/12/049/16/04

Keywords

  • Fuzzy logic
  • State estimation

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Holbert, K., & Lin, K. (2004). Reducing state estimation uncertainty through fuzzy logic evaluation of power system measurements. In 2004 International Conference on Probabilistic Methods Applied to Power Systems (pp. 205-211). (2004 International Conference on Probabilistic Methods Applied to Power Systems).