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Electrical Engineering
Erschienen in: Electrical Engineering 1/2021

01.08.2020 | Original Paper

A random forest-based approach for fault location detection in distribution systems

verfasst von: Hatice Okumus, Fatih M. Nuroglu

Erschienen in: Electrical Engineering | Ausgabe 1/2021

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Abstract

Finding the fault location in distribution network is difficult in comparison to transmission network based upon high branching and high impedances composed of the contact with environmental factors when a fault occurs. For this matter, the possible faulty section is identified and then the fault location is determined with the proposed algorithms in this study. Wavelet transform is applied to the current–voltage data along with feature extraction methods, and then, Random Forest is used for identifying the faulty section and estimating the fault location. To approve the validation, the algorithms are applied to IEEE-34 node test feeder. Single-phase to ground faults regarding different impedance values at different points of the feeder have been effectively detected by using single measurement point data from the sending end of the feeder.
Vorheriger Artikel Direct approach for optimal allocation of multiple capacitors in distribution systems using novel analytical closed-form expressions
Nächster Artikel A novel strategy for frequency control of islanded greenhouse with cooperative usage of BESS and LED lighting loads

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Literatur
1.
Das S, Santoso S, Gaikwad A, Patel M (2014) Impedance-based fault location in transmission networks: theory and application. IEEE Access 2:537–557CrossRef
2.
Salim RH, Salim KCO, Bretas AS (2011) Further improvements on impedance-based fault location for power distribution systems. IET Gener Transm Distrib 5(4):467–478CrossRef
3.
Yuan L (2011) Generalized fault-location methods for overhead electric distribution systems. IEEE Trans Power Delivery 26(1):53–64CrossRef
4.
Aboshady FM, David WPT, Sumner M (September 2017) Fast fault location scheme for distribution systems based on fault transients. In: International Conference on Resilience of Transmission and Distribution Networks, Birmingham, UK
5.
Das S, Santoso S, Maitra A (July 2014) Effects of distributed generators on impedance-based fault location algorithms. In: PES General Meeting| Conference & Exposition, National Harbor, USA
6.
Mora-Flórez JJ, Herrera-Orozco RA, Bedoya-Cadena AF (2015) Fault location considering load uncertainty and distributed generation in power distribution systems. IET Gener Transm Distrib 9(3):287–295CrossRef
7.
Gururajapathy SS (2017) Fault location in distribution systems using mathematical analysis and support vector machine, PhD thesis, University of Malaya
8.
Yan F, Liu W, Tian L (September 2011) Fault location for 10 kV distribution line based on traveling wave-ANN theory. In: Conference on IEEE Power Engineering and Automation, Wuhan, China, pp 437–440
9.
Hai-Qing L, Hao Z (July 2011) Lightning strike location of 10 kV distribution feeder based on traveling wave theory. In: 24th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Weihai, China
10.
Qianqian L, Zeng X, Xue M et al (October 2013) A new smart distribution grid fault self-healing system based on traveling-wave. In: Industry Applications Society Annual Meeting, Lake Buena Vista, USA
11.
Ye H, Rui K, Zhu ZK et al (November 2015) A novel single-phase grounding fault location method with traveling wave for distribution networks. In: 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Changsha, China
12.
Gururajapathy SS, Mokhlis H, Illias HAB (2018) Classification and regression analysis using support vector machine for classifying and locating faults in a distribution system. Turkish J Electrical Eng Comput Sci 26(3):3044–3056
13.
da Silva Pessoa AL, Oleskovicz M, Martins PET (May 2018) A multi-stage methodology for fault location in radial distribution systems. In: 18th International Conference on Harmonics and Quality of Power (ICHQP) IEEE, Ljubljana, Slovenia
14.
Tong Z, Lanxiang S, Jianchang L et al (2018) Fault diagnosis and location method for active distribution network based on artificial neural network. Electric Power Component Syst 46(9):985–996
15.
Ray P, Mishra DP (July 2015) Signal processing technique-based fault location of a distribution line. In: IEEE 2nd international conference on recent trends in information systems (ReTIS), Kolkata, India
16.
Adewole AC, Tzoneva R, Behardien S (2016) Distribution network fault section identification and fault location using wavelet entropy and neural networks. Appl Soft Comput 46:296–306CrossRef
17.
Aslan Y (2012) An alternative approach to fault location on power distribution feeders with embedded remote-end power generation using artificial neural networks. Electr Eng 94(3):125–134CrossRef
18.
Aslan Y, Yağan YE (2017) Artificial neural-network-based fault location for power distribution lines using the frequency spectra of fault data. Electr Eng 99(1):301–311CrossRef
19.
Goudarzi M, Vahidi B, Naghizadeh RA et al (2015) Improved fault location algorithm for radial distribution systems with discrete and continuous wavelet analysis. Int J Electr Power Energy Syst 67:423–430CrossRef
20.
Zhao J, Xia X, Su D et al (2019). Fault section location method based on random forest algorithm for distribution networks with distribution generations. In: IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), Chengdu, China
21.
Morales-España G, Mora-Flórez J, Vargas-Torres H (2009) Elimination of multiple estimation for fault location in radial power systems by using fundamental single-end measurements. IEEE Trans power Delivery 24(3):1382–1389CrossRef
22.
Kim CH, Aggarwal R (2001) Wavelet transforms in power systems. II. Examples of application to actual power system transients. Power Eng J 15(4):193–202CrossRef
23.
Shanks, J.L., “Computation of the fast Walsh-Fourier transform”, IEEE Transactions on Computers, 1969, vol. 100, no. 5, pp. 457-459, 1969
24.
25.
Pal M (2005) Random forest classifier for remote sensing classification. Int J Remote Sens 26(1):217–222CrossRef
26.
Watts JD, Powell SL, Lawrence RL et al (2011) Improved classification of conservation tillage adoption using high temporal and synthetic satellite imagery. Remote Sens Environ 115(1):66–75CrossRef
27.
Breiman L (2002) Manual on setting up, using, and understanding random forests v3. 1. Statistics Department University of California Berkeley, California
28.
Metadaten
Titel
A random forest-based approach for fault location detection in distribution systems
verfasst von
Hatice Okumus
Fatih M. Nuroglu
Publikationsdatum
01.08.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 1/2021
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-020-01074-8

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