Abstract
Background: A new DWT-ERT-based fault location method is suggested in the
IEEE test feeder.
Objective: The fault location approach in the distribution network has been proposed in this paper
that utilizes the discrete wavelet transform (DWT) and ensemble regression tree (ERT).
Methods: The fault location methodology has been validated by simulations conducted on an
IEEE 13 bus node test feeder.
Results: The results show that the suggested solution has low compute burden and memory requirements,
and is unaffected by system and fault situations.
Conclusion: In this study, the fault location approach for the distribution system employing
DWT and ERT has been proposed.
Keywords:
Fault location, distribution systems, discrete wavelet transform, ensemble regression tree, power outage, artificial neural network.
[1]
M. McGranaghan, T. Short, and D. Sabin, "Using PQ monitoring infrastructure for automatic fault location", In 19th International Conference on Electricity Distribution, 2007.
[2]
IEEE Guide for Determining Fault Location on AC Transmission and Distribution Lines, IEEE Std, vol. C37, p. 114, 2014.
[6]
L.W. Xie, Y. Li, L.F. Luo, C. Chen, and Y.J. Cao, "Distribution network fault location method based on distance matrix and branch coefficient", In Proceedings of the Chinese Society for Electrical Engineering, 2022.
[14]
D. Thukaram, and H.P. Khincha, "Artificial neural network and support vector Machine approach for locating faults in radial distribution systems", IEEE Trans. Power Deliv., vol. 20, no. 2, pp. 710-721, 2005.
[23]
J. Dang, Y. Yan, R. Jia, X. Wang, and H. Wei, "Fast single-phase fault location method based on community graph depth-first traversal for distribution network", CSEE J. Power Energy Syst., vol. 9, no. 2, pp. 612-622, 2021.
[24]
B. Yang, K. Jia, Q. Liu, L. Zheng, and T. Bi, "Faulted line section location in distribution system with inverter interfaced DGs using sparse meters", IEEE Trans. Smart Grid, vol. 14, no. 1, pp. 413-423, 2022.