http://iet.metastore.ingenta.com
1887

Hyperbolic S-transform-based method for classification of external faults, incipient faults, inrush currents and internal faults in power transformers

Hyperbolic S-transform-based method for classification of external faults, incipient faults, inrush currents and internal faults in power transformers

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Generation, Transmission & Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In this study, a hyperbolic S-transform-based method is proposed to discriminate most important transient fault currents of transformers. First, the proposed method discriminates external faults from other disturbances. Then, the S-transform is applied to differential currents. An index is suggested by using absolute deviations of the S-matrix of differential currents to discriminate internal incipient faults in addition to inrush currents and internal faults. The relay issues an alarm signal in the case of the incipient fault but restrains during the magnetising inrush current. If an internal fault is recognised, the relay will issue a trip signal. To study the robustness of the suggested method, a program is developed in the MATLAB environment. The inputs of this program are differential current signals, derived from a system modelled by EMTP software. In order to simulate the internal incipient fault along with internal turn to turn and turn to earth faults, the transformer is modelled as 8×8 RL matrices, derived by using subroutine BCTRAN in EMTP. Also, differential currents are contaminated by noise and it is shown that the suggested method is not affected by noise and it can discriminate incipient faults, inrush currents, internal faults and external faults.

References

    1. 1)
      • Butler-Purry, K.L., Wang, H.: `Computer models of internal short circuit and incipient faults in transformers', IEEE PES Transmission and Distribution Conf. and Exposition, 2003, p. 1027–1027.
    2. 2)
    3. 3)
      • Prema Kumar, N., Amarnath, J., Shrivastava, K.D., Singh, B.P.: `Identification of winding faults in power transformers by low voltage impulse test and neutral current method using wavelet transform approach', Annual Report Conf. on Electrical Insulation and Dielectric Phenomena, CEIDP 05, October 2005, p. 140–143.
    4. 4)
      • Chang, C.S., Lim, C.W., Su, Q.: `Fuzzy-neural approach for dissolved gas analysis of power transformers incipient faults', Australasian Universities Power Engineering Conf. (AUPEC), September 2004, Brisbane, Australia.
    5. 5)
    6. 6)
    7. 7)
    8. 8)
    9. 9)
      • T.F. Lee , M.Y. Cho , C.S. Shieh , H.J. Lee , F.M. Fang . Diagnosis of incipient fault of power transformers using SVM with clonal selection algorithms optimization.
    10. 10)
    11. 11)
      • de Aquino, R.B., Lira, M.M.S., Filgueiras, T., Ferreira, H.: `A fuzzy system for detection of incipient fault in power transformer based on gas-in-oil analysis', IEEE Int. Conf. on Fuzzy Systems, 2010, p. 1–6.
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
      • Butler-Purry, K.L., Bagriyanik, M.: `Identifying transformer incipient events for maintaining distribution system reliability', Proc. 36th Annual Int. Conf. on System Sciences, 2003, Hawaii.
    17. 17)
      • Geethanjali, M., Slochanal, S.M.R., Bhavani, R.: `A novel approach for power transformer protection based upon combined wavelet transform and neural networks (WNN)', Seventh Int. Power Engineering Conf., November–December 2005, p. 1–6.
    18. 18)
      • Hoang Viet, N., Tuan Dung, N.: `New approach for classifying transient phenomena in power transformer using discrete wavelet transforms (DWT) and fuzzy logic', Int. Symp. on Electrical and Electronics Engineering, October 2007, HCM City, Vietnam, p. 261–265.
    19. 19)
      • Kargar, H.K., Jabbari, M., Golmohammad Zadeh, S.: `Inrush current identification based on wavelet transform and correlation factors', Sixth Int. Conf. on Telecommunication and Technology, 2009, p. 50–53.
    20. 20)
    21. 21)
    22. 22)
      • S. Subramanian , M. Badrilal , J. Henry . Wavelet transform based differential protection for power transformer and classification of faults using SVM and PNN. Int. Rev. Electr. Eng. , 5 , 2186 - 2198
    23. 23)
      • Zhang, Q., Jiao, S., Wang, S.: `Identification inrush current and internal faults of transformer based on Hyperbolic S-transform', Fourth Conf. on Industrial Electronics and Applications, 2009, p. 258–263.
    24. 24)
      • Panigrahi, B.K., Samantaray, S.R., Dash, P.K., Panda, G.: `Discrimination between inrush current and internal faults using pattern recognition approach', Int. Conf. on power Electronics, Drives and Energy Systems, 2006, p. 1–5.
    25. 25)
    26. 26)
      • Jia, S., Wang, S., Zheng, G.: `A new approach to identify inrush current based on generalized S-transform', Int. Conf. on Electrical Machines and Systems, 2008, p. 4317–4322.
    27. 27)
      • Sendilkumar, S., Mathur, B.L., Henry, J.: `A new technique to classify transient events in power transformer differential protection using S-transform', Third Int. Conf. on Power Systems, 2009, Kharagpur, INDIA, p. 1–6.
    28. 28)
    29. 29)
      • S.H. Horowitz , A.G. Phadke . (1992) Power system relaying.
    30. 30)
      • Oliveira, M.O., Salim, R.H., Bretas, A.S.: `Differential protection of three-phase transformers using wavelet transforms', IEEE PES Transmission and Distribution Conf. and Exposition, 2008, Latin America, p. 1–5.
    31. 31)
    32. 32)
      • A. Ngaopitakkul , A. Kunakorn . Internal fault classification in transformer windings using combination of discrete wavelet transforms and back-propagation neural networks. Int. J. Control Autom. Syst. , 3 , 365 - 371
    33. 33)
    34. 34)
      • Sabihaand, A., Izzularab, M.A.: `Transformer modeling with internal incipient', 11thInt. Middle East Power Systems Conf., December 2006, p. 117–122.
    35. 35)
      • Mousavi, J., Butler-Purry, K.L.: `Transformer internal incipient fault simulations', North American Power Symp., October 2003, Rolla, MO, p. 195–203.
    36. 36)
      • ANSI/IEEE Standard C57.13: ‘Requirements for instrument transformers’, 1978.
    37. 37)
      • Rifaat, M.R.: `Considerations in applying EMTP to evaluate current transformer performance under transient and high current fault conditions', Int. Conf. on Power Systems Transient (IPST 05), June 2005, Montreal, Canada.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2012.0047
Loading

Related content

content/journals/10.1049/iet-gtd.2012.0047
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address