DocumentCode :
3641080
Title :
Setting strategy of a SVM regressor for locating single phase faults in power distribution systems
Author :
E. Correa-Tapasco;S. Perez-Londoño;J. Mora-Florez
Author_Institution :
Universidad Tecnoló
fYear :
2010
Firstpage :
798
Lastpage :
802
Abstract :
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.
Keywords :
"Fault location","Support vector machines","Genetic algorithms","Power distribution","Circuit faults","Electrical engineering","Optimization"
Publisher :
ieee
Conference_Titel :
Transmission and Distribution Conference and Exposition: Latin America (T&D-LA), 2010 IEEE/PES
Print_ISBN :
978-1-4577-0488-8
Type :
conf
DOI :
10.1109/TDC-LA.2010.5762976
Filename :
5762976
Link To Document :
بازگشت