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Recent Advances in Electrical & Electronic Engineering

Editor-in-Chief

ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

Research Article

Traveling-wave-based Fault Location using Time Delays between Modal Components in Electrical Distribution Systems

Author(s): Yang Lei, Fan Yang, Zhijiang Yin, Jinrui Tang*, Guoqing Zhang, Bo Ma, Yu Shen and Zhichun Yang

Volume 17, Issue 8, 2024

Published on: 04 October, 2023

Page: [778 - 786] Pages: 9

DOI: 10.2174/2352096516666230816123406

Price: $65

Abstract

Background: The distribution feeders usually include many laterals, too many sensors need to be installed to locate the fault positions in electrical distribution systems by using the traditional double-ended traveling-wave-based fault-location methods.

Objective: Fault location based on the time delays between the moments of the first wavefronts of zero-mode voltages and that of aerial-mode voltages arriving at one end of the distribution feeder.

Methods: Large decomposition level in wavelet transformation is adopted in this paper to obtain the zero-mode velocity.

Results: Both theoretical research and simulation experiments have proved that the proposed fault location method can greatly improve the accuracy of the fault location in the electrical distribution systems without many sensors.

Conclusion: The proposed fault location method can provide one feasible way to locate the faults in the electrical distribution systems.

Graphical Abstract

[1]
F.V. Lopes, K.M. Silva, F.B. Costa, W.L.A. Neves, and D. Fernandes, "Real-time traveling-wave-based fault location using two-terminal unsynchronized data", IEEE Trans. Power Deliv., vol. 30, no. 3, pp. 1067-1076, 2015.
[http://dx.doi.org/10.1109/TPWRD.2014.2380774]
[2]
F.M. de Magalhaes Junior, and F.V. Lopes, "Mathematical study on traveling waves phenomena on three phase transmission lines – Part II: Reflection and refraction matrices", IEEE Trans. Power Deliv., vol. 37, no. 2, pp. 1161-1170, 2022.
[http://dx.doi.org/10.1109/TPWRD.2021.3077730]
[3]
J. Wang, and Y. Zhang, "Traveling wave propagation characteristic-based LCC-MMC hybrid HVDC transmission line fault location method", IEEE Trans. Power Deliv., vol. 37, no. 1, pp. 208-218, 2022.
[http://dx.doi.org/10.1109/TPWRD.2021.3055840]
[4]
A. Abd el-Ghany Hossam, and M. Azmy Ahmed, "A general travelling-wave-based scheme for locating simultaneous faults in transmission lines", IEEE Trans. Power Deliv., vol. 35, no. 1, pp. 130-139, 2020.
[http://dx.doi.org/10.1109/TPWRD.2019.2931178]
[5]
O.D. Naidu, and A.K. Pradhan, "Precise traveling wave-based transmission line fault location method using single-ended data", IEEE Trans. Industr. Inform., vol. 17, no. 8, pp. 5197-5207, 2021.
[http://dx.doi.org/10.1109/TII.2020.3027584]
[6]
H. Jia, "An improved traveling-wave-based fault location method with compensating the dispersion effect of traveling wave in wavelet domain", Math. Probl. Eng., vol. 2017, pp. 1-11, 2017.
[http://dx.doi.org/10.1155/2017/1019591]
[7]
W. Chen, D. Wang, D. Cheng, and X. Liu, "Travelling wave fault location approach for MMC-HVDC transmission line based on frequency modification algorithm", Int. J. Electr. Power Energy Syst., vol. 143, p. 108507, 2022.
[http://dx.doi.org/10.1016/j.ijepes.2022.108507]
[8]
M.M. Zarachoff, A. Sheikh-Akbari, and D. Monekosso, "Non-decimated wavelet based multi-band ear recognition using principal component analysis", IEEE Access, vol. 10, pp. 3949-3961, 2022.
[http://dx.doi.org/10.1109/ACCESS.2021.3139684]
[9]
X. Zheng, Y. Zeng, M. Zhao, and B. Venkatesh, "Early identification and location of short-circuit fault in grid-connected AC microgrid", IEEE Trans. Smart Grid, vol. 12, no. 4, pp. 2869-2878, 2021.
[http://dx.doi.org/10.1109/TSG.2021.3066803]
[10]
M. Jia, F. Li, J. Wu, Z. Chen, and Y. Pu, "Robust QRS detection using high-resolution wavelet packet decomposition and time-attention convolutional neural network", IEEE Access, vol. 8, pp. 16979-16988, 2020.
[http://dx.doi.org/10.1109/ACCESS.2020.2967775]
[11]
K. Naidu, M.S. Ali, A.H. Abu Bakar, C.K. Tan, H. Arof, and H. Mokhlis, "Optimized artificial neural network to improve the accuracy of estimated fault impedances and distances for underground distribution system", PLoS One, vol. 15, no. 1, p. e0227494, 2020.
[http://dx.doi.org/10.1371/journal.pone.0227494] [PMID: 31999711]
[12]
J.M. Li, S.C. Chu, X. Shao, and J-S. Pan, "A single-phase-to-ground fault location method based on convolutional deep belief network", Electr. Power Syst. Res., vol. 209, p. 108044, 2022.
[http://dx.doi.org/10.1016/j.epsr.2022.108044]
[13]
M. Jiménez-Aparicio, J. Hernández-Alvidrez, A.Y. Montoya, and M.J. Reno, "Embedded, real-time, and distributed traveling wave fault location method using graph convolutional neural networks", Energies, vol. 15, no. 20, p. 7785, 2022.
[http://dx.doi.org/10.3390/en15207785]
[14]
R. Mardiana, H.A. Motairy, and C.Q. Su, "Ground fault location on a transmission line using high-frequency transient voltages", IEEE Trans. Power Deliv., vol. 26, no. 2, pp. 1298-1299, 2011.
[http://dx.doi.org/10.1109/TPWRD.2010.2091327]
[15]
D. Akmaz, and M.S. Mamiş, "Fault location method on two-terminal transmission line using synchronized time information of traveling waves", Electr. Eng., vol. 104, no. 2, pp. 979-990, 2022.
[http://dx.doi.org/10.1007/s00202-021-01356-9]
[16]
Y. Wang, A.O. Rousis, and G. Strbac, "A three-level planning model for optimal sizing of networked microgrids considering a trade-off between resilience and cost", IEEE Trans. Power Syst., vol. 36, no. 6, pp. 5657-5669, 2021.
[http://dx.doi.org/10.1109/TPWRS.2021.3076128]

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