Classification methodology and feature selection to assist fault location in power distribution systems

  • Juan José Mora-Flórez Universidad Tecnológica de Pereira
  • Germán Morales-España Universidad Tecnológica de Pereira
  • Sandra Pérez-Londoño Universidad Tecnológica de Pereira
Keywords: distribution systems, fault location, power quality, signal characterization, support vectors


A classification methodology based on Support Vector Machines (SVM) is proposed to locate the faulted zone in power distribution networks. The goal is to reduce the multiple-estimation problem inherent in those methods that use single end measures (in the substation) to estimate the fault location in radial systems. A selection of features or descriptors obtained from voltages and currents measured in the substation are analyzed and used as input of the SVM classifier. Performance of the fault locator having several combinations of these features has been evaluated according to its capability to discriminate between faults in different zones but located at similar distance. An application example illustrates the precision, to locate the faulted zone, obtained with the proposed methodology in simulated framework. The proposal provides appropriate information for the prevention and opportune attention of faults, requires minimum investment and overcomes the multiple-estimation problem of the classic impedance based methods.

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Author Biographies

Juan José Mora-Flórez, Universidad Tecnológica de Pereira

Grupo de Investigación en Calidad de Energía Eléctrica y Estabilidad (ICE) - Programa de Ingeniería Eléctrica

Germán Morales-España, Universidad Tecnológica de Pereira

Grupo de Investigación en Calidad de Energía Eléctrica y Estabilidad (ICE) - Programa de Ingeniería Eléctrica

Sandra Pérez-Londoño, Universidad Tecnológica de Pereira

Grupo de Investigación en Calidad de Energía Eléctrica y Estabilidad (ICE)- Programa de Ingeniería Eléctrica


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How to Cite
Mora-Flórez J. J., Morales-España G., & Pérez-Londoño S. (2014). Classification methodology and feature selection to assist fault location in power distribution systems. Revista Facultad De Ingeniería Universidad De Antioquia, (44), 83-96. Retrieved from