By Topic

Setting strategy of a SVM regressor for locating single phase faults in power distribution systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Correa-Tapasco, E. ; Univ. Tecnol. de Pereira, Pereira, Colombia ; Perez-Londono, S. ; Mora-Florez, J.

In this paper, a regression technique as the support vector machines (SVM) configured using an optimization technique as the Chu Beasley Genetic Algorithm (CBGA) is proposed to develop a fault location method. As result, a strategy is proposed to relate a set of descriptors obtained from single end measurements of voltage and current (input), to the fault location (output), in a classical regression task. The developed strategy is tested in the selection of the best calibration parameters of a single phase SVM based fault locator where an average error of 5.278% is then obtained. According to the results, the proposed methodology could be applied successfully in power distribution systems.

Published in:

Transmission and Distribution Conference and Exposition: Latin America (T&D-LA), 2010 IEEE/PES

Date of Conference:

8-10 Nov. 2010