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High impedance fault detection based on current harmonic analysis using Chirp Z transform

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Abstract

High Impedance Fault (HIF) is a problematic fault of feeders which its fault current is lower as compared to normal current in power system. Likewise, due to magnitude of impedance engaged in fault area and behavior of fault current is specific and not the same as the usual fault current profile which cannot be identified by standard relays. The HIF is created whenever a live conductor contacts with objects owning large impedance. The HIFs Signal has high index of similarity with some normal cases in feeders like Nonlinear loads (NL) waveform, or instant of switching of linear loads (LL), capacitor banks (CB) and full load transformers (FLT), which provided methods must distinguish them. So, the paper utilized a novel method with ability of recognizing HIF from all possible events in feeders with high accuracy. The Chirp Z Transform (CZT) has been applied to extract the features of HIF and/or other usual network events signal. It is possible to appropriately detect fault by low order harmonics of current signal extracted by means of CZT. Maximum discrepancy of detection is nearly 7 ms which is accurate enough. Also, absence of threshold values in algorithm makes it simple and can be used in each type of distribution and even transmission systems. Working in low-frequency harmonics is another advantage of this method because needs lower sampling frequency. The evaluated signals of HIF, NLs, LLs, capacitors and FLT are acquired by a simulated 13.8 kV distribution system in MATLAB/Simulink.

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References

  1. Wester, C.G.: High impedance fault detection on distribution system. IEEE Rural Electric Power Conf. 1–5 (1998)

  2. Lee, R., Bishop, M.: performance testing of the ratio ground relay on a four wire distribution feeder. IEEE Trans. Power App. And sys. 102, 2943–2949 (1983)

    Article  Google Scholar 

  3. Sarlak, M., Shahtash, S.M.: High impedance faulted branch identification using magnetic field signature analysis. IEEE Trans. Power Delivery. 28(1), 67–74 (2013)

    Article  Google Scholar 

  4. Gautam, S., Brahma, S.M.: Detection of high impedance fault in power distribution system using mathematical morphology. IEEE Trans. Power delivery. 28(2), 1226–1234 (2013)

    Article  Google Scholar 

  5. Snider, L.A., Yuen, Y.S.: ANN based relay algorithm for detection of high impedance fault. Neurocoputing. 23, 243–254 (1998)

    Article  Google Scholar 

  6. Eissa, M.M., Sowilam, G.M.A., Sharaf, A.M. (2006): A new protection detection technique for high impedance fault using neural network. Power Engineering IEEE Large Engineering Systems Conference. 146–151

  7. Aziz, M.A., Hassan, M.M., Zahab, E.A.: High-impedance faults analysis in distribution networks using an adaptive neuro fuzzy inference system. Electric Power Compon. Syst. 40(11), 1300–1318 (2012)

    Article  Google Scholar 

  8. Samantaray, S.R.: Ensemble decision trees for high impedance fault detection in power distribution network. Int. J. Elect. Power Energy Syst. 43(1), 1048–1055 (2012)

    Article  Google Scholar 

  9. David W Chan tat, Xia, Y.: A novel technique for high impedance fault Identification. IEEE Trans. Power Del. 13, 738–744 (1998)

  10. Moravej, Z., Mortazavi, S.H., Shahrtash, S.M.: DT-CWT based event feature extraction for high impedance faults detection in distribution system. Int. Trans. Elec. Energy Syst. 25, 3288–3303 (2015)

    Article  Google Scholar 

  11. Ghaderi, A., Mohammadpour, H., Ginn, H., Shin, Y.: High impedance fault detection in distribution network using time-frequency based algorithm. IEEE Trans. Power Deliv. 30(3), 1260–1268 (2014)

    Article  Google Scholar 

  12. Sarlak, M., Shahrtash, S.M., Arab-Khaburi, D.: Design and implementation of a systematically tunable high impedance fault relay. ISA Trans. 49(3), 358–368 (2010)

    Article  Google Scholar 

  13. Sedighi, A.R., Haghifam, M., Malik, O.P., Ghassemian, M.H.: High impedance fault detection based on wavelet transform and statistical pattern recognition. IEEE Trans. Power delivery. 20(4), 2414–2421 (2005)

    Article  Google Scholar 

  14. Sahoo, S., Baran, M.E.: A method to detect high impedance faults indistribution feeders. in: T D Conference and Exposition. 2014 IEEE PES. 1–6 (2014).

  15. Samantaray, S., Panigrahi, K., Dash, P.: High impedance fault detection in power distribution networks using time-frequency transform and probabilistic neural network. IET Gener. Transm. Distrib. 2(2), 261–270 (2008)

    Article  Google Scholar 

  16. Wang, X., et al.: High impedance fault detection method based on variational mode decomposition and teager-kaiser energy operators for distribution network. IEEE Trans. Smart Grid. 10(6), 6041–6054 (2019)

    Article  Google Scholar 

  17. Thomas, M.S., Bhaskar, N., Prakash, A.: Voltage based detection method for high impedance fault in a distribution system. J. Institution Eng. 97, 413–423 (2016)

    Google Scholar 

  18. Gadanayak, D.A., Mallick, R.K.: Interharmonics based high impedance fault detection in distribution systems using maximum overlap wavelet packet transform and a modified empirical mode decomposition. Int. J. Elect. Power Energy Syst. 112, 282–293 (2019)

    Article  Google Scholar 

  19. Mortazavi, S.H., Moravej, Z., Shahrtash, S.M.: A hybrid method for arcing faults detection in large distribution networks. Int. J. Elect. Power Energy Syst. 94, 141–150 (2018)

    Article  Google Scholar 

  20. Oppenheim, A.V., Shafer, R.W.: Digital signal processing. 784p, Englewood cliffs NJ, prentice hall (1975)

  21. Aiello, M., Cataliotti, A., Nuccio, S.: A Chirp Z transform based synchronizer for power systems measurement. IEEE Trans. Inst. Meas. 54(3), 1025–1032 (2005)

    Article  Google Scholar 

  22. Aiello, M., Cataliotti, A., Cosentino, V., Nuccio, S.: Synchronization techniques for power quality instruments. IEEE Trans. Inst. Meas. 56(5), 1511–1519 (2007)

    Article  Google Scholar 

  23. Diao, R., Meng, Q.: An interpolation algorithm for discrete Fourier transforms of weighted damped sinusoidal signals. IEEE Trans. Inst. Meas. 63(6), 1505–1513 (2014)

    Article  Google Scholar 

  24. Orallo, C.M., Carugati, I., et al.: Harmonics measurement with a modulated sliding discrete Fourier transform algorithm. IEEE Trans. Inst. Meas. 63(4), 781–793 (2014)

    Article  Google Scholar 

  25. Aiello, M., Cataliotti, A., Nuccio, S.: A comparison of spectrum estimation technique for periodic and not stationary signals. Proc. IMTC. 2, 1130–1134 (2001)

    Google Scholar 

  26. Artale, G., Cataliotti, A., et al.: Arc fault detection method based on CZT low frequency harmonic current analysis. IEEE Trans. Inst. Meas. 66(5), 888–896 (2017)

    Article  Google Scholar 

  27. Wang, T.T.: The segmented chirp z transform and its application in spectrum analysis. IEEE Trans. Inst. Meas. 39(2), 318–323 (1990)

    Article  Google Scholar 

  28. Chen, J.C., Phung, B.T., Zhang, D.M., Blackburn, T., Ambikairajah, E.: Study on high impedance fault arcing current characteristics. 2013 Australasian Universities Power Engineering Conf. (2013)

  29. Elkalashy, N., Lehtonen, M., Darwish, H.A., et al.: Modeling and experimental verification of high impedance arcing fault in medium voltage networks. IEEE Trans. Dielectr. Electr. Insul. 14(2), 375–383 (2007)

    Article  Google Scholar 

  30. Costa, F.B., Souza, B.A., Brito, N.S.D., et al.: Real-time detection of transients induced by high-impedance faults based on the boundary wavelet transform. IEEE Trans. Ind. Appl. 51(6), 5312–5323 (2015)

    Article  Google Scholar 

  31. Sarwagya, K., De, S., Nayak, P.K.: High impedance fault detection in electrical power distribution system using moving sum approach. IET Sci. Meas. Tech. 12(1), 1–8 (2018)

    Article  Google Scholar 

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Authors and Affiliations

  1. Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran

    Mojtaba Karimi & Navid Ghaffarzadeh

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  1. Mojtaba Karimi
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  2. Navid Ghaffarzadeh
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Correspondence to Navid Ghaffarzadeh.

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Karimi, M., Ghaffarzadeh, N. High impedance fault detection based on current harmonic analysis using Chirp Z transform. Energy Syst 13, 813–833 (2022). https://doi.org/10.1007/s12667-021-00431-1

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