Feeder-level fault detection and classification with multiple sensors: a smart grid scenario

No Thumbnail Available
Issue Date
2014
Embargo End Date
Authors
Wang, Nan
Aravinthan, Visvakumar
Ding, Yanwu
Advisor
Citation

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

Abstract

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.

Table of Content
Description
Click on the DOI link to access the article (may not be free).
publication.page.dc.relation.uri
DOI