Title :
An intelligent approach using SVM to enhance turn-to-turn fault detection in power transformers
Author :
Elsamahy, Mohamed ; Babiy, M.
Author_Institution :
Dept. of Electr. Power & Energy, Mil. Tech. Coll., Cairo, Egypt
Abstract :
This paper proposes the use of the SVMs classification technique for power transformer protection, in order to enhance the detection of minor internal turn-to-turn faults. The proposed scheme has been also tested through external faulted cases as well as energizing inrush phenomenon. In addition, it has been compared with a conventional differential algorithm. The results have shown that the proposed intelligent technique provides fast, sensitive and reliable detection of minor internal turn-to-turn faults in power transformers. The dynamic simulations of a test benchmark have been conducted using the PSCAD/EMTDC software.
Keywords :
fault diagnosis; power engineering computing; power transformers; support vector machines; PSCAD-EMTDC software; SVM classification technique; conventional differential algorithm; dynamic simulations; intelligent approach; power transformers; turn-to-turn fault detection enhancement; Circuit faults; Kernel; Power transformers; Support vector machines; Testing; Training; Windings; Transformer protection; internal turn-to-turn faults; support vector machines;
Conference_Titel :
Electrical Power and Energy Conference (EPEC), 2012 IEEE
Conference_Location :
London, ON
Print_ISBN :
978-1-4673-2081-8
Electronic_ISBN :
978-1-4673-2079-5
DOI :
10.1109/EPEC.2012.6474961
