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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2010 - 3

 HIGH-IMPACT PAPER 

A New Protection Scheme for High Impedance Fault Detection using Wavelet Packet Transform

GHAFFARZADEH, N. See more information about GHAFFARZADEH, N. on SCOPUS See more information about GHAFFARZADEH, N. on IEEExplore See more information about GHAFFARZADEH, N. on Web of Science, VAHIDI, B. See more information about VAHIDI, B. on SCOPUS See more information about VAHIDI, B. on SCOPUS See more information about VAHIDI, B. on Web of Science
 
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Download PDF pdficon (540 KB) | Citation | Downloads: 1,769 | Views: 6,816

Author keywords
artificial neural network, distribution networks, fault detection, high impedance fault, wavelet packet

References keywords
power(22), high(15), fault(15), impedance(14), detection(14), delivery(12), wavelet(6), distribution(6), system(4), networks(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2010-08-31
Volume 10, Issue 3, Year 2010, On page(s): 17 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.03003
Web of Science Accession Number: 000281805600003
SCOPUS ID: 77956620776

Abstract
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Full text preview
This paper proposed a novel technique to effectively discriminate between the HIF and the normal system operation events in distribution by combining a preprocessing module based on wavelet packet transform with an artificial neural network(ANN). Wavelet packet is firstly applied to extract of distinctive feature of current signals. Then this information is introduced to training ANN for identifying an HIF from the normal system operation events. The simulated results clearly show that the proposed technique can accurately identify the HIF in overhead distribution feeder.


References | Cited By  «-- Click to see who has cited this paper

[1] M. A. Aucoin, and B. D. Russel, "Distribution high impedance Detection utilizing high frequency components", IEEE Transaction on Power Apparatus and System, vol. 101, no. 6, pp. 1596-1606, 1982.
[CrossRef] [Web of Science Times Cited 86] [SCOPUS Times Cited 148]


[2] M. A. Aucoin, B. D. Russel, and C. L. Benner, "High impedance fault Detection for industrial power systems", in Proc. of IEEE Industry Applications Society Annual Meeting, vol. 2, pp. 1788-1792, 1989.
[CrossRef] [Web of Science Times Cited 12]


[3] M. A. Aucoin, "Status of high impedance fault detection", IEEE Transaction on Power Apparatus and System, vol. 104, no. 3, pp. 638-643, 1985.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 13]


[4] C. G. Wester, "High impedance fault detection on distribution systems", In Proc. Of 1998 Rural Electric Power Conference, pp. c5-1-5, 1998.
[CrossRef]


[5] S. Ebron, D. L. Lubkeman, and M. White, "A neural network approach to the detection of incipient faults on power distribution feeders", IEEE Trans. on Power Delivery, vol. 5, no. 2, pp. 905-914, 1990.
[CrossRef] [Web of Science Times Cited 118] [SCOPUS Times Cited 175]


[6] A. F. Sultan, G. W. Swift, and D. J. Fedirchuk, "Detecting arcing downed -wires using fault current flicker and half cycle asymmetry", IEEE Transactions on Power Delivery, vol. 9, no. 1, pp. 461-470, 1994.
[CrossRef] [Web of Science Times Cited 102] [SCOPUS Times Cited 129]


[7] D. Jeering, and J. R. Linders, "Ground resistive-revisited", IEEE Transactions on Power Delivery, vol. 4, no. 2, pp. 949-956, 1989.
[CrossRef] [Web of Science Times Cited 34] [SCOPUS Times Cited 28]


[8] P. R. Silva, A. Santos, W. C. Boaventura, G. C. Miranda, and J. A. Scott, "Impulse response analysis of a real feeder for high impedance fault detection", in Proc. of 1994 IEEE Int. Conf. on Transmission and distribution, pp. 276-283, 1994.
[CrossRef] [Web of Science Times Cited 5]


[9] W. H. Kown, G. W. Lee, Y. M. Park, M. C. Yoon, and M. H. Yoo, "High impedance fault detection utilizing incremental variance of normalized even order harmonic power", IEEE Transactions on Power Delivery, vol. 6, no. 2, pp. 557-564, 1991.
[CrossRef] [SCOPUS Times Cited 99]


[10] B. D. Russell, R. P. Chinchali, and C. J. Kim, "Behavior of low frequency current components performance evalution using recorders field data", IEEE Transactions on Power Delivery, vol. 3, no. 4, pp. 1485-1492, 1988.
[CrossRef] [Web of Science Times Cited 41] [SCOPUS Times Cited 57]


[11] B. D. Russell, K. Mehta, and R. P. Chinchali, "An arcing fault detection technique using low frequency current components performance evalution using recorders field data", IEEE Transactions on Power Delivery, vol. 3, no. 4, pp. 1493-1500, 1988.
[CrossRef] [Web of Science Times Cited 46] [SCOPUS Times Cited 68]


[12] R. Christie, H. Zadhgole, and M. Habib, "High impedance fault detection in low voltage networks", IEEE Transactions on Power Delivery, vol. 8, no. 4, pp. 1829-1836, 1993.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 29]


[13] F. Ruz, and J. A. Fuentes, "Fuzzy decision making applied to high impedance fault detection in compensated neutral grounded MV distribution systems", in Proc. of 2001 IEE Conf. on Developments in Power System Protection, pp. 307-310, 2001.
[CrossRef]


[14] F. G. Jota, and P. R. S. Jota, "High-impedance fault identification using a fuzzy reasoning system", IEE Proc.-Gener.Transm.Distrib, vol. 145, no. 6, pp. 656-662, 1998.
[CrossRef] [Web of Science Times Cited 31] [SCOPUS Times Cited 45]


[15] Jae-Ho. KO, Jae-Chul. Shim, Chang-Wan Ryu, Chan-Gook Park, and Wha-Yeong Yim, "Detection of high impedance fault using neural nets and chaotic degree", in Proc. of 1998 IEEE Energy Management and Power Deliver, vol. 2, pp. 399-404, 1998.
[CrossRef]


[16] R. Keyhani, M. Deriche, and E. Palmer, "A high impedance fault detector using a neural network and subband decomposition", in Proc. of 2001 IEEE Conference On Signal Processing and Its Applications, pp. 458-461, 2001.
[CrossRef] [SCOPUS Times Cited 23]


[17] Chul-Hwan Kim, Hyun Kim, Young-Hun Ko, Sung-Hyun Byun, Raj K. Aggarwal, and Allan T. Johns, "A novel fault-detection technique of high-impedance arcing faults in transmission lines using the wavelet transform", IEEE Transactions on Power Delivery, vol. 17, no. 4, pp. 921-929, 2002.
[CrossRef] [Web of Science Times Cited 135] [SCOPUS Times Cited 184]


[18] T. M. Lai, L. A. Snider, and E. Lo. D. Sutanto, "High-impedance fault detection using discrete wavelet transform and frequency range and RMS conversion", IEEE Transactions on Power Delivery, vol. 20, no. 1, pp. 397-407, 2005.
[CrossRef] [Web of Science Times Cited 158] [SCOPUS Times Cited 220]


[19] M. Michalik, M. Lukowicz, W. Rebizant, S-J. Lee, S-H. Kang, "Verification of the wavelet-based HIF detecting algorithm performance in solidly grounded MV networks", IEEE Transactions on Power Delivery, vol. 22, no. 4, pp. 2057-2064, 2007.
[CrossRef] [Web of Science Times Cited 29] [SCOPUS Times Cited 39]


[20] M. Michalik, W. Rebizant, M. Lukowicz, S. J. Lee, and S. H. Hang, "High impedance fault detection in distribution networks with use of wavelet based algorithm", IEEE Transactions on Power Delivery, vol. 21, no. 4 , pp. 1793-1802, 2006.
[CrossRef] [Web of Science Times Cited 128] [SCOPUS Times Cited 164]


[21] S. A. Saleh, "A Wavelet Packet Transform-Based Differential Protection of Three-Phase Power Transformers," Master's Thesis, Memorial Univ. Newfoundland, St. John's, NF, Canada, 2003.

[22] E. Y. Hamid and Z. I. Kawasaki, "Wavelet-based data compression for power disturbances using minimum description length data," IEEE Transactions on Power Delivery, vol. 17, no. 2, pp. 460-466, Apr. 2002.
[CrossRef] [Web of Science Times Cited 121] [SCOPUS Times Cited 166]


[23] Eduardo D. Sontag, "Feedback Stabilization Using Two-Bidden-Layer Nets," IEEE Trans. Neur. Networks, vol. 3 no. 6, pp. 981-990, 1992.
[CrossRef] [PubMed] [Web of Science Times Cited 118] [SCOPUS Times Cited 137]


References Weight

Web of Science® Citations for all references: 1,214 TCR
SCOPUS® Citations for all references: 1,724 TCR

Web of Science® Average Citations per reference: 53 ACR
SCOPUS® Average Citations per reference: 75 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-12-03 23:02 in 166 seconds.




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