Thukaram, D and Shenoy, UJ and Ashageetha, H (2006) Neural network approach for fault location in unbalanced distribution networks with limited measurements. In: IEEE Power India Conference 2006,, Apr 10-12, 2006, New Delhi, India, pp. 493-500.
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Abstract
This paper presents an Artificial Neural Network (ANN) approach for locating faults in distribution systems. Different from the traditional Fault Section Estimation methods, the proposed approach uses only limited measurements. Faults are located according to the impedances of their path using a Feed Forward Neural Networks (FFNN). Various practical situations in distribution systems, such as protective devices placed only at the substation, limited measurements available, various types of faults viz., three-phase, line (a, b, c) to ground, line to line (a-b, b-c, c-a) and line to line to ground (a-b-g, b-c-g, c-a-g) faults and a wide range of varying short circuit levels at substation, are considered for studies. A typical IEEE 34 bus practical distribution system with unbalanced loads and with three- and single- phase laterals and a 69 node test feeder with different configurations are considered for studies. The results presented show that the proposed approach of fault location gives close to accurate results in terms of the estimated fault location.
Item Type: | Conference Paper |
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Publisher: | IEEE |
Additional Information: | Copyright 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Keywords: | Distribution automation;fault location;feed forward neural network and radial basis probabilistic neural;network. |
Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
Date Deposited: | 27 Aug 2010 05:40 |
Last Modified: | 19 Sep 2010 06:12 |
URI: | http://eprints.iisc.ac.in/id/eprint/30498 |
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