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Fault location based on FastICA and fuzzy C-means clustering for single-phase-to-ground fault in the compensated distribution network

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Abstract

A new method for fault location during a single-phase-to-ground fault in the compensated distribution network is proposed in this paper. The method makes full use of the difference between transient-state fault information and the difference between steady-state fault information in two FTUs (feeder terminal units) of each section to determine faulty location. In this method, the transient-state component and steady-state component of zero-sequence current measured by each FTU are extracted by FastICA (fast independent component analysis) algorithm and are represented by the transient-state factor and steady-state factor, which are defined in this paper. Then, the difference between transient-state factors and the difference between steady-state factors in two FTUs of each section are calculated. The two differences corresponding to a certain section are seen as a feature vector, which is given as one input to the fuzzy C-means (FCM) algorithm. All feature vectors will be partitioned into two clusters, one of which represents a faulty section, and the other of which represents a healthy section. As a result, faulty location will be determined. Simulation results show the effectiveness and reliability of the proposed method under different fault conditions.

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References

  1. Sagastabeitia KJ, Zamora I, Mazon AJ et al (2012) Low-current fault detection in high impedance grounded distribution networks, using residual variation of asymmetries. IET Gener Transm Distrib 6(12):1252–1261

    Article  Google Scholar 

  2. Wanying H, Kaczmarek R (2007) SLG fault detection in presence of strong capacitive currents in compensated networks. IEEE Trans Power Del 22(4):2132–2135

    Article  Google Scholar 

  3. Welfonder T, Leitloff V, Feuillet V et al (2000) Location strategies and evaluation of detection algorithms for earth faults in compensated MV distribution systems. IEEE Trans Power Del 15(4):1121–1128

    Article  Google Scholar 

  4. **angjun Z, Li KK, Chan WL et al (2008) Ground-fault feeder detection with fault-current and fault-resistance measurement in mine power systems. IEEE Trans Ind Appl 44(2):424–429

    Article  Google Scholar 

  5. Topolanek D, Matti M, Adzman MR et al (2015) Earth fault location based on evaluation of voltage sag at secondary side of medium voltage/low voltage transformers. IET Gener Transm Distrib 9(14):2069–2077

    Article  Google Scholar 

  6. Coffele F, Booth C, Dyśko A (2015) An adaptive overcurrent protection scheme for distribution networks. IEEE Trans Power Del 30(2):561–568

    Article  Google Scholar 

  7. Ying Z, **aoning K, Zaibin J et al (2014) A novel distance protection algorithm for the phase-ground fault. IEEE Trans Power Del 29(4):1718–1725

    Article  Google Scholar 

  8. Mora-Florez J, Melendez J, Carrillo-Caicedo G (2008) Comparison of impedance based fault location methods for power distribution systems. Elect Power Syst Res 78(4):657–666

    Article  Google Scholar 

  9. Jia K, Thormas D, Sumner M (2012) Impedance-based earth fault location for a non-directly grounded distribution systems. IET Gener Transm Distrib 6(12):1272–1280

    Article  Google Scholar 

  10. Zaizhong S, Huifen Z, Zhencun P (1996) Single-phase earthed faulty line selection protection using injected signal in non-solidly grounded systems. Power Syst Autom, pp 11–12

  11. Druml G, Raunig C, Schegner P, et al (2012) Earth fault localization with the help of the fast-pulse-detection-method using the new high-power-current-injection (HPCI). Electric power quality and supply reliability conference (PQ), pp 1–5

  12. Benteng H, Wei** H (1998) A new principle to detect the grounded line in a neutral point indirectly grounded power system based on the energy function. Zhejiang Univ 32(4):451–456

    Google Scholar 

  13. **jie L, Yulin Q, Shihao S (2013) Single phase to ground fault location based on phase of zero-sequence current. In: Proceedings of international conference on information and automation, pp 856–859

  14. Linli Z, Houlei G, Bingyin X (2012) Fault location method based on zero sequence admittance measurement in non-effectively earthed system. In: Proceedings of IEEE PES innovative smart grid technologies, pp 1–4

  15. Linli Z, Bingyin X, Yongduan X et al (2012) Transient fault locating method based on line voltage and zero-mode current in non-solidly earthed network. Porc CSEE 32(13):110–115

    Google Scholar 

  16. Tao T, Chun H, Yaqun J et al (2016) Fault line selection method in resonant earthed system based on transient signal correlation analysis under high and low frequencies. Autom Electric Power Syst 40(16):105–111

    Google Scholar 

  17. Tao C, **nzhou D, Zhiqian B et al (2011) Hilbert-transform-based transient/intermittent earth fault detection in noneffectively grounded distribution systems. IEEE Trans Power Del 26(1):143–151

    Article  Google Scholar 

  18. Huan Y, Kexin R, Zikun Z, et al (2011) A novel single-phase grounding fault location method with traveling wave for distribution networks. In: Proceedings of 5th international conference on electric utility deregulation and restructuring and power technologied (DRPT), pp 1175–1179

  19. Dong X, Shi S (2008) Identifying single-phase-to-ground fault feeder in neutral noneffectively grounded distribution system using wavelet transform’. IEEE Trans Power Del 23(4):1829–1837

    Article  Google Scholar 

  20. Shu Z, Jianwei Y, Zhengyou H et al (2015) Fault section location of the distribution network based on transient center frequency. Porc CSEE 35(10):2460–2470

    Google Scholar 

  21. Awalin LJ, Mokhlis H, Halim AHA (2012) Improved fault location on distribution network based on multiple measurements of voltage sags pattern. In: IEEE international conference power and energy (PECon), pp 767–772

  22. Zhixia Z, **ao L, Zailin P (2014) Fault line detection in neutral point ineffectively grounding power system based on phase-locked loop. IET Gener Transm Distrib 8(2):273–280

    Article  Google Scholar 

  23. Yajie L, **aoli M, **aohui S (2016) Application of signal processing and analysis in detecting single line-to-ground (SLG) fault location in high-impedance grounded distribution network. IET Gener Transm Distrib 18(2):382–389

    Google Scholar 

  24. Yuanyuan W, Jiaming Z, Zewen L et al (2015) Discriminant-analysis-based single-phase earth fault protection using improved PCA in distribution systems. IEEE Trans Power Del 30(4):1974–1982

    Article  Google Scholar 

  25. Tianyou L, Yongduan X, Juanjuan L, et al (2013) A new single phase fault location method of non-effectively grounded networks for DA systems. In: Proceedings of 22th international conference on electricity distribution, pp 1–4

  26. Ma SC, Xu BY, Bo ZQ et al (2013) Transient current correlation based single phase earth fault location for distribution automation. In Proceedings of 45th international universities power engineering conference, pp 1–4

  27. Assef Y, Bastard P, Meunier M (1996)Artificial neural networks for single phase fault detection in resonant grounded power distribution systems. In: Proceedings of 22th transmission distribution conference, pp 566–572

  28. Shu H, Qiu G, Li C, et al (2010) A fault line selection algorithm using neural network based on S-transform energy. In: Proceedings of 6th international conference on natural computation, 2010, pp 1478–1482

  29. ** Z, Honggeng Y (2016) A new method to calculate the utility harmonic impedance based on FastICA’. IEEE Trans Power Del 31(1):381–388

    Article  Google Scholar 

  30. Zaixin Z, Lizhi C, Guangquan C (2014) Neighbourhood weighted fuzzy c-means clustering algorithm for image segmentation’. IET Image Process 8(3):150–161

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant 52207075 and the Natural Science Foundation of Hunan Province under Grant 2023JJ30036.

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Authors and Affiliations

  1. Hunan Province Key Laboratory of Smart Grids Operation and Control, Changsha University of Science and Technology, Changsha, 410114, China

    Tao Tang, Yu Zhou, **angjun Zeng & **aohan Li

  2. Hunan Electric Power Transmission and Transformation Engineering Co., Ltd, Changsha, 410015, China

    Chunhui Luo

Authors
  1. Tao Tang
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  2. Yu Zhou
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  3. **angjun Zeng
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  4. Chunhui Luo
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  5. **aohan Li
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Correspondence to Yu Zhou.

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Tang, T., Zhou, Y., Zeng, X. et al. Fault location based on FastICA and fuzzy C-means clustering for single-phase-to-ground fault in the compensated distribution network. Electr Eng 105, 4079–4093 (2023). https://doi.org/10.1007/s00202-023-01933-0

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