Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Identification of Partial Discharge Defects based on Back- Propagation Algorithm in Eco-friendly Insulation Gas

  • Sung-Wook Kim (Department of Electrical and Electronics Engineering, Silla University)
  • Received : 2023.06.11
  • Accepted : 2023.06.21
  • Published : 2023.09.30
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Abstract

This study presents a method for identifying partial discharge defects in an eco-friendly gas insulated system using a backpropagation algorithm. Four partial discharge (PD) electrode systems, namely, a free-moving particle, protrusion on the conductor, protrusion on the enclosure, and voids, were designed to simulate PD defects that can occur during the operation of eco-friendly gas-insulated switchgear. The PD signals were measured using an ultrahigh-frequency sensor as a nonconventional method based on IEC 62478. To identify the types of PD defects, the PD parameters of single PD pulses in the time and frequency domains and the phase-resolved partial discharge patterns were extracted, and a back-propagation algorithm in the artificial neural network was designed using a virtual instrument based on LabVIEW. The backpropagation algorithm proposed in this paper has an accuracy rate of over 90% for identifying the types of PD defects, and the result is expected to be used as a reference database for asset management and maintenance work for eco-friendly gas-insulated power equipment.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant number: 2022R1G1A1011043).

References

  1. S. W. Kim, J. R. Jung, Y. M. Kim, G. S. Kil, and G. Wang, "New diagnosis method of unknown phase-shifted PD signals for gas insulated switchgears," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 25, no. 1, pp. 102-109, Feb. 2018. DOI: 10.1109/TDEI.2018.006739.
  2. G. M. Wang and G. S. Kil, "Measurement and analysis of partial discharge using an ultra-high frequency sensor for gas insulated structures," Metrology and Measurement Systems, vol. 24, no. 3, pp. 515-524, Sep. 2017. DOI: 10.1515/mms-2017-0045.
  3. A. Beroual and A. Haddad, "Recent advances in the quest for a new insulation gas with a low impact on the environment to replace sulfur hexafluoride (SF6) gas in high-voltage power network applications," Energies, vol. 10, no. 8, p. 1216, Aug. 2017. DOI: 10.3390/en10081216.
  4. Intergovernmental Panel on Climate Change. Cambridge University Press: New York, NY, USA, pp. 159-254, 2013.
  5. F. Ye, X. Zhang, Y. Li, Y. Li, Z. Wei, S. Xiao, and S. Tian, "AC breakdown strength and its by-products of eco-friendly perfluoroiso-butyronitrile/O2/N2 Gas Mixture at High Pressure for HV Equipment," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 28, no. 3, pp. 1020-1027, Jun. 2021. DOI: 10.1109/TDEI.2021.009463.
  6. B. Zhang, N. Uzelac, and Y Cao, "Fluoronitrile/CO2 mixture as an eco-friendly alternative to SF6 for medium voltage switchgears," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 25, no. 4, pp. 1340-1350, Aug. 2018. DOI: 10.1109/TDEI.2018.007146.
  7. G. Wang, W. H. Kim, G. S. Kil, S. W. Kim, and J. R. Jung, "Green gas for a grid as an eco-friendly alternative insulation gas to SF6: from the perspective of partial discharge under AC," Applied Sciences, vol. 9, no. 4, p. 651, Feb. 2019. DOI: 10.3390/app9040651.
  8. H. E. Nechmi, A. Beroual, A. Girodet, and P. Vinson, "Effective ionization coefficients and limiting field strength of fluoronitrilesCO2 mixtures," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 24, no. 2, pp. 886-892, Apr. 2017. DOI: 10.1109/TDEI.2017.006538.
  9. Y. Kieffel, T. Irwin, P. Ponchon, and J. Owens, "Green gas to replace SF6 in Electrical Grids," IEEE Power and Energy Magazine, vol. 14, no. 2, pp. 32-39, Mar. 2016. DOI: 10.1109/MPE.2016.2542645.
  10. H. E. Nechmi, A. Beroual, A. Girodet, and P. Vinson, "Fluoronitriles/CO2 gas mixture as promising substitute to SF6 for insulation in high voltage applications," IEEE Transactions on Dielectrics and Electrical Insulation, vol. 23, no. 5, pp. 2587-2593, Oct. 2016. DOI: 10.1109/TDEI.2016.7736816.
  11. A. Beroual and A. Haddad, "Recent advances in the quest for a new insulation gas with a low impact on the environment to replace sulfur hexafluoride (SF6) gas in high-voltage power network applications," Energies, vol. 10, no. 8, p. 1216, Aug. 2017. DOI: 10.3390/en10081216.
  12. CIGRE Working Group D1.33. Guide for Partial Discharge Measurements in Compliance to IEC 60270; Technical Brochure No. 366, CIGRE Paris, France, 2008.
  13. H. D. Ilkhechi and M. H. Samimi, "Application of the acoustic method in partial discharge measurement: A review," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 28, no. 1, pp. 42-51, Feb. 2021. DOI: 10.1109/TDEI.2020.008985.
  14. A. Lapp and H. G. Kranz, "The use of the CIGRE data format for PD diagnosis applications," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 7, no. 1, pp. 102-112, Feb. 2000. DOI: 10.1109/ 94.839347.
  15. W. Y. Chang, "Partial discharge pattern recognition of cast resin current transformers using radial basis function neural network," Journal of Electrical Engineering and Technology, vol. 9, no. 1, pp. 293-300, Jan. 2014. DOI: 10.5370/JEET.2014.9.1.293.
  16. M. N. Danikas, N. Gao, and M. Aro, "Partial discharge recognition using neural network: A review," Electrical Engineering, vol. 85, pp. 87-95, May 2003. DOI: 10.1007/s00202-002-0151-5.
  17. N. Hozumi, T. Okamoto, and T. Imajo, "Discrimination of partial discharge patterns using neural network," IEEE Transaction on Dielectrics and Electrical Insulation, vol. 27, no. 3, pp. 550-556, Jun. 1992. DOI: 10.1109/14.142718.