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Journal of Vibration Testing and System Dynamics

C. Steve Suh (editor), Pawel Olejnik (editor),

Xianguo Tuo (editor)

Pawel Olejnik (editor)

Lodz University of Technology, Poland

Email: pawel.olejnik@p.lodz.pl

C. Steve Suh (editor)

Texas A&M University, USA

Email: ssuh@tamu.edu

Xiangguo Tuo (editor)

Sichuan University of Science and Engineering, China

Email: tuoxianguo@suse.edu.cn


A New Fault Locating Algorithm for T-splice Transmission Lines based on Back-ward Traveling Wave

Journal of Vcibration Testing and System Dynamics 3(3) (2019) 313--328 | DOI:10.5890/JVTSD.2019.09.005

Hao Wu, Xingxing Dong, Qiaomei Wang

Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, China

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Abstract

Existing fault locating algorithms for T-splice transmission lines are hugely susceptible to traveling wave velocity. To address this issue, this paper presents a new fault locating algorithm for T-splice transmission lines based on the initial voltage backward traveling wave. In this algorithm, the three-terminal busbar initial voltage backward traveling waves are collected and S-transform is implemented to analyze the ratio of voltage amplitude and construct discriminant of the faulted transmission line. Once the faulted branch is detected, three-terminal line is converted into two-terminal line. The fault range locating algorithm can be developed by using line parameters and the time initial traveling wave used to reach the three-terminal busbar. The algorithm making it less susceptible to swing amid the uncertainty of traveling wave velocity and overcomes the shortcomings of the unreliability of traditional method for detecting the faulted line near T node. Simulation results demonstrate high accuracy of the algorithm, which is less susceptible to the changes in fault types, transitional resistances, initial fault angles and other factors.

Acknowledgments

This research was supported by the artificial intelligence key laboratory of Sichuan province Foundation (2017RYY02), and the Project of Sichuan provincial science and Technology Department (Grant No. 2017JY0338, 2019YJ0477, 2018GZDZX0043), Enterprise informatization and Internet of things measurement and control technology key laboratory project of Sichuan provincial university (2018WZY01), Sichuan University of Science and Engineering talent introduction project (2017RCL53) and the Project of Sichuan Provincial Academician (Expert) workstation of Sichuan University of Science and Engineering (2018YSGZZ04).

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