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Induced Voltages Ratio-Based Algorithm for Fault Detection, and Faulted Phase and Winding Identification of a Three-Winding Power Transformer

Authors :
Jung-Wook Park
Yong Cheol Kang
Byung Eun Lee
Peter Crossley
Source :
Energies, Volume 7, Issue 9, Pages: 6031-6049, Energies, Vol 7, Iss 9, Pp 6031-6049 (2014), ENERGIES(7): 9
Publication Year :
2014
Publisher :
Multidisciplinary Digital Publishing Institute, 2014.

Abstract

This paper proposes an algorithm for fault detection, faulted phase and winding identification of a three-winding power transformer based on the induced voltages in the electrical power system. The ratio of the induced voltages of the primary-secondary, primary-tertiary and secondary-tertiary windings is the same as the corresponding turns ratio during normal operating conditions, magnetic inrush, and over-excitation. It differs from the turns ratio during an internal fault. For a single phase and a three-phase power transformer with wye-connected windings, the induced voltages of each pair of windings are estimated. For a three-phase power transformer with delta-connected windings, the induced voltage differences are estimated to use the line currents, because the delta winding currents are practically unavailable. Six detectors are suggested for fault detection. An additional three detectors and a rule for faulted phase and winding identification are presented as well. The proposed algorithm can not only detect an internal fault, but also identify the faulted phase and winding of a three-winding power transformer. The various test results with Electromagnetic Transients Program (EMTP)-generated data show that the proposed algorithm successfully discriminates internal faults from normal operating conditions including magnetic inrush and over-excitation. This paper concludes by implementing the algorithm into a prototype relay based on a digital signal processor.

Details

Language :
English
ISSN :
19961073
Database :
OpenAIRE
Journal :
Energies
Accession number :
edsair.doi.dedup.....71efc030e22ba30754502c93bc8f0e6c
Full Text :
https://doi.org/10.3390/en7096031