A support vector machine (SVM) based voltage stability classifier

Rodel D. Dosano, Hwachang Song, Byongjun Lee

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

Abstract

This paper proposes a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. The excellent performance of the SVM in the classification related to time-series prediction matches the real-time data of local measurement for system responses by shortterm and long-term dynamics. The methodology for automatic monitoring of the system is initiated locally, which aims to leave sufficient time to perform immediate corrective actions to stop system degradation by the effect of major disturbances. This paper explains the procedure for fast classification of long-term voltage stability using the SVM algorithm.

Original languageEnglish
Title of host publicationProceedings of the 7th IASTED International Conference on Power and Energy Systems
Pages265-271
Number of pages7
Publication statusPublished - 2007 Dec 1
Event7th IASTED International Conference on Power and Energy Systems - Palma de Mallorca, Spain
Duration: 2007 Aug 292007 Aug 31

Publication series

NameProceedings of the IASTED International Conference on Energy and Power Systems

Other

Other7th IASTED International Conference on Power and Energy Systems
CountrySpain
CityPalma de Mallorca
Period07/8/2907/8/31

Keywords

  • Classification
  • Local phasor measurement
  • Power system voltage stability
  • Real-time monitoring
  • Support vector machine

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Condensed Matter Physics

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  • Cite this

    Dosano, R. D., Song, H., & Lee, B. (2007). A support vector machine (SVM) based voltage stability classifier. In Proceedings of the 7th IASTED International Conference on Power and Energy Systems (pp. 265-271). (Proceedings of the IASTED International Conference on Energy and Power Systems).