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논문 상세정보


Substation facilities have become extremely large and complex parts of electric power systems. The development of condition monitoring and diagnosis techniques has been a very significant factor in the improvement of substation transformer security. This paper presents a method to analyze the cause, the degree, and the aging process power transformers by the Self Organizing Map (SOM) method. Dissolved gas data were non-linearly transformed by the sigmoid function in SOM that works much the same way as the human decision making process. The potential for failure and the degree of aging of normal transformers are identified by using the proposed quantitative criterion. Furthermore, transformer aging is monitored by the proposed criterion for a set of transformers. To demonstrate the validity of the proposed method, a case study is performed and its results are presented.

참고문헌 (16)

  1. Y Kashima, 'Automatic Field Monitoring of Dissolved Gases in Transformer Oil', IEEE Trans., Vol. PAS-100, pp. 1538-1544, 1981 
  2. H. Tsukioka, K. Sugawara, E. Mori, S. Hukumori and S. Sakai, 'New Apparatus for Detecting H2, CO and CH4 Dissolved in Transformer Oil', IEEE Transaction on Electrical Insulation, Vol. EI-13, No. 4, pp. 409-419, 1983 
  3. Hong Tzer Yang, Yann Chang Huang, 'Intelligent Decision Support for Diagnosis of Incipient Transformer Faults Using Self-Organizing Polynomial Networks', IEEE Transaction on Power Systems, Vol. 13, No. 3, pp. 946-952, August. 1998 
  4. LiMin Fu, Neural Network in computer Intelligence, McGraw-Hill, pp. 48-55, 1994 
  5. R. R. Rogers, 'IEEE and IEC Code To Interpret Incipient Faults in Transformers Using Gas in Oil Analysis', IEEE Transaction on Electrical Insulation, Vol. EI-13, No. 5, pp. 349-354, 1978 
  6. H. Yoshida, Y. Ishioka, T. Suzuki, T. Yanari and T. Teranishi, 'Degradation of Insulating Materials of Transformers', IEEE Transaction on Electrical Insulation, Vol. EI-22, No. 6, pp. 795-800, 1987 
  7. Philip D. Wasserman, Neural Computer Theory and Practice, Van. Mostrand Reinold, pp. 64-70, 1989 
  8. W. Xu, D. Wang, Z. Zhou, H. Chen, 'Fault Diagnosis of Power Transformers: Application of Fuzzy Set Theory, Expert Systems and Artificial Neural Networks', IEE Proc.-Sci Meas. Technol., Vol. 144, No. 1, pp. 39-44, January. 1997 
  9. J.P. Lee, P.S. Ji, S.C. Nam, J.Y. Lim, 'Aging Characteristics of Power Transformer Oil and Development of It's Analysis Using KSOM', in Proceedings of ICEE 98, Vol. II, Kyongju, Korea, pp. 461-464, July. 1998 
  10. H. Tsukioka, K. Sugawara, E. Mori and H. Yamaguchi, 'New Apparatus For Detecting Transformer Faults', IEEE Transaction on Electrical Insulation, Vol. EI-21, No. 2, pp. 221-229, 1986 
  11. C. E. Lin, J. M. Ling, C. L. Huang, 'An Expert System for Transformer Fault Diagnosis Using Dissolved Gas Analysis', IEEE Transaction on Power Delivery, Vol. 8, No. 1, pp. 231-238, January 1993 
  12. M. Duval, 'Dissolved Gas Analysis: It Can Save Your Transformer', IEEE Electrical Insulation Magazine, Vol. 5, No. 6, pp. 22-26, 1989 
  13. Y. Kamata, 'Diagnostic Methods for Power Transformer Insulation', IEEE Transaction on Electrical Insulation, Vol. EI-21, No. 6, pp. 1045-1048, 1986 
  14. Zhenyuan Wang, Yilu Liu, P.J. Griffin, 'A Combined ANN and Expert System Tool for Transformer Fault Diagnosis', IEEE Transaction on Power Delivery, Vol. 13, No. 4, pp. 1224-1229, October. 1998 
  15. Y. C. Huang, H. T. Yang, C. L. Huang, 'Developing a New Transformer Fault Diagnosis System Through Evolutionary Fuzzy Logic', IEEE Transaction on Power Delivery, Vol. 12, No. 2 pp. 761-767, April. 1997 
  16. Y. Zhang, X. Ding, Y. Liu, P.J. Griffin, 'An Artificial Neural Network Approach to Transformer Fault Diagnosis', IEEE Transaction on Power Delivery, Vol. 11, No. 4, pp. 1836-1842, October. 1996 

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