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.
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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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Agreira, C.I.F., Ferreira, C.M.M., Barbosa, F.P.M. (2013). Rough Set Theory: Data Mining Technique Applied to the Electrical Power System. In: Madureira, A., Reis, C., Marques, V. (eds) Computational Intelligence and Decision Making. Intelligent Systems, Control and Automation: Science and Engineering, vol 61. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4722-7_36
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DOI: https://doi.org/10.1007/978-94-007-4722-7_36
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