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Rough Set Theory: Data Mining Technique Applied to the Electrical Power System

  • C. I. Faustino Agreira
  • C. M. Machado Ferreira
  • F. P. Maciel Barbosa
Conference paper
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 61)

Abstract

This paper presents a study were the Rough Set Theory and Data Mining Technique are applied to the electrical power system. The Data Mining technique classifies the system operation in four possible states: normal, alert, emergency (emergency I and emergency II). The states, that correspond to the normal state can be classified as secure and insecure the remaining ones. In this security studies, the overloads in transmition lines and the violation of the voltage limits are used to classify and rank these contingencies. This technique was applied to the 118IEEE busbar test power network and the results obtained are analyzed. Finally, some conclusions that provide a valuable contribution to the understanding of the power system security analysis are pointed out.

Keywords

Data Mining Technique Electrical Power System Decision Attribute Classification Strength Indiscernibility Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The first author would like to thank “Fundação para Ciência e Tecnologia, FCT”, that partially funded this research work through the PhD grant nº: SFRH/BD/38152/2007.

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • C. I. Faustino Agreira
    • 1
  • C. M. Machado Ferreira
    • 1
    • 2
  • F. P. Maciel Barbosa
    • 3
  1. 1.Departamento de Engenharia ElectrotécnicaInstituto Superior de Engenharia de CoimbraCoimbraPortugal
  2. 2.INESCCoimbraPortugal
  3. 3.INESC Tech, Faculdade de Engenharia da Universidade do PortoPortoPortugal

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