A Study on the Fault Current Discrimination Using Enhanced Fuzzy C-Means Clustering

개선된 퍼지 C-Means 클러스터링을 이용한 고장전류판별에 관한 연구

  • Published : 2008.11.01

Abstract

This paper demonstrates a enhanced FCM to identify the causes of ground faults in power distribution systems. The discrimination scheme which can automatically recognize the fault causes is proposed using Fuzzy RBF networks. By using the actual fault data, it is shown that the proposed method provides satisfactory results for identifying the fault causes.

Keywords

References

  1. Aucoin B.M., Hussell B.D., 'Dustribution High Impedance Fault Detection Utlizing High Frequecy Current Components', IEEE Trans. on Power Appartus and Systems Vol. Pas-101, No. 6, pp. 1596-1606, June 1982 https://doi.org/10.1109/TPAS.1982.317209
  2. 이준탁, 정종원, '웨이블릿 변환을 이용한 전력시스템 고장전류의 판별', 조명.설비학회 논문지, 제21권 3호, pp.75-81, 2007, 3월 https://doi.org/10.5207/JIEIE.2007.21.3.075
  3. Martin T. Haugan, 'Neural Network Design', PWS Publishing Company, 1996
  4. M. L. Kothari, S. Madnari and R. Segal, 'Othogonal Least Square Learning Algorithm Based Radial Basis Function Network Adaptive Power System Stabilizer', Proceedings of IEEE SMC, Vol. 1, pp. 542-547, 1997
  5. R.L. Cannon, J.V. Dave, and J.C. Bezdk, 'Efficient Implementation of Fuzzy C Means Clustering Algorithm,' IEEE Trans. Pater Anal. & Machine Int., Vol. PAMI-8, No.2, pp. 248-255, 1986 https://doi.org/10.1109/TPAMI.1986.4767778
  6. Arun D.K., Computer Vision and Fuzzy - Neual Systems, Prentice Hall PTR, 2001
  7. J. bezdek, 'A convergence theorem for the Fuzzy ISODATA clustering algorithm', IEEE Trans. Pater Anal Machine Intell., Vol. PAMI-2, No. 1, pp.1-8, 1980 https://doi.org/10.1109/TPAMI.1980.4766964
  8. 2006 보호계전기 동작상태 분석 보고서, 한국전력공사 송변전처 변전운영팀, 2006