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Impedance-Based Fault Location Algorithm for Ground Faults in Series-Capacitor-Compensated Transmission Lines

Locating a fault in a series-capacitor-compensated transmission line (SCCTL) is a challenging task due to the action of a metal-oxide varistor a nonlinear element present as a part of the protection system of the series capacitor. In this paper, an accurate fault-location algorithm that uses synchro...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2018-02, Vol.33 (1), p.189-199
Main Authors: Bains, Tirath Pal S., Sidhu, Tarlochan S., Xu, Zhihan, Voloh, Ilia, Zadeh, Mohammad R. Dadash
Format: Article
Language:English
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Summary:Locating a fault in a series-capacitor-compensated transmission line (SCCTL) is a challenging task due to the action of a metal-oxide varistor a nonlinear element present as a part of the protection system of the series capacitor. In this paper, an accurate fault-location algorithm that uses synchronized measurements from both ends of the SCCTL is presented which provides fault-location results without using the model of MOV or natural fault loop for single-phase-to-ground, and double-phase-to-ground faults. Another salient feature of the proposed technique is that the subroutines for locating faults in different sections transmission line yield almost identical fault-location results regardless of which section the transmission line is faulted. The proposed technique could also be extended to the double-circuit transmission lines. First, the proposed technique is introduced and its features are elaborated through detailed mathematical analysis. Thereafter, a 500-\text{kV} system with an SCCTL is designed in PSCAD, while the fault-location algorithm is modeled in MATLAB. The proposed algorithm is tested through simulations covering various fault scenarios in an SCCTL. For performance evaluation, the comparative analysis of the proposed technique with a well-known existing technique is performed in this paper.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2017.2711358