Unique localization of faults in distribution systems by means of zones with SVM
DOI:
https://doi.org/10.17533/udea.redin.17765Keywords:
Descriptors, artificial intelligence, fault’s localization, multiple estimation, distribution systems, SVM, zonesAbstract
This paper presents a new methodology for localizing faults in distribution systems by means of an artificial intelligence technique –Support Vector Machine– (SVM). This methodology divides the electrical system into different zones order to pinpoint the region where the fault exists with accuracy. The advantage over classical distance methods is the unique estimation of the fault’s locus in branches systems. An example using a real system model shows that the proposed methodology is highly effective finding the fault localization. In such example load changes of ±40 % from nominal load are considered.
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