Feeder-level fault detection and classification with multiple sensors: a smart grid scenario
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Nan Wang; Aravinthan, V.; Yanwu Ding. 2014. Feeder-level fault detection and classification with multiple sensors: A smart grid scenario. Statistical Signal Processing (SSP), 2014 IEEE Workshop on Year: 2014 Pages: 37 - 40
The smart grid initiative requires self-healing distribution systems with more accurate fault detection and classification techniques. A multi-sensor feeder-level fault detection and classification algorithm is presented in this work, based on the techniques of the support vector machine and the principal components. An IEEE 34-bus feeder model with dynamic loading conditions is used to evaluate the developed algorithm. Noise in the three-phase current measurements is applied. The numerical analysis indicates that high accuracies in fault detection and classification are achieved for the proposed algorithm.
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