International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Application of Similarity Measure for Fuzzy C-Means Clustering to Power System Management

  • Park, Dong-Hyuk (School of Mechatronics, Changwon National University) ;
  • Ryu, Soo-Rok (Department of Industrial and Applied mathematics, Kyungbuk National University) ;
  • Park, Hyun-Jeong (Department of Mathematics Education, Ewha Woman University) ;
  • Lee, Sang-H. (School of Mechatronics, Changwon National University)
  • Published : 2008.03.01
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Abstract

A FCM with locational price and regional information between locations are proposed in this paper. Any point in a networked system has its own values indicating the physical characteristics of that networked system and regional information at the same time. The similarity measure used for FCM in this paper is defined through the system-wide characteristic values at each point. To avoid the grouping of geometrically distant locations with similar measures, the locational information are properly considered and incorporated in the proposed similarity measure. We have verified that the proposed measure has produced proper classification of a networked system, followed by an example of a networked electricity system.

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References

  1. W. Li and A. Bose, "A coherency based rescheduling method for dynamic security", IEEE Transactions on Power Systems, Vol. 13, No. 3, pp. 810-815, 1998 https://doi.org/10.1109/59.708662
  2. S.K. Joo, C.C. Liu, L.E. Jones, and J.W. choe, "Coherency and aggregation techniques incorporating rotor and voltage dynamics", IEEE Transactions on Power Systems, Vol. 19, No. 2, pp. 1068-1075, 2004 https://doi.org/10.1109/TPWRS.2004.825825
  3. A.M. Gallai and R.J. Thomas, "Coherency Identification for large electric power systems", IEEE Transactions on Circuits and Systems, Vol. CAS-29, No. 11, pp. 777-782, 1982
  4. F.F. Wu. N. Narasmithamurthi, "Coherency Identification for power system dynamic equivalents", IEEE Transactions on Circuits and Systems, Vol. CAS-30, No. 3, pp. 140-147, 1983
  5. Liu Xuecheng, "Entropy, distance measure and similarity measure of fuzzy sets and their relations", Fuzzy Sets and Systems, Vol. 52, pp. 305-318, 1992 https://doi.org/10.1016/0165-0114(92)90239-Z
  6. J. L. Fan, W. X. Xie, "Distance measure and induced fuzzy entropy," Fuzzy Set and Systems, Vol. 104, pp. 305-314, 1999 https://doi.org/10.1016/S0165-0114(99)80011-6
  7. J. L. Fan, Y. L. Ma, and W. X. Xie, "On some properties of distance measures," Fuzzy Set and Systems, Vol. 117, pp. 355-361, 2001 https://doi.org/10.1016/S0165-0114(98)00387-X
  8. S.H. Lee, S.P. Cheon, and Jinho Kim, "Measure of certainty with fuzzy entropy function", LNAI, Vol. 4114, pp. 134-139, 2006
  9. S.H. Lee, J.M. Kim, and Y.K. Choi, "Similarity measure construction using fuzzy entropy and distance measure", LNAI, Vol.4114, 952-958, 2006
  10. J.C. Bezdek, Fuzzy Mathematics in Pattern Classification, Ph.D Thesis, Applied Math. Center, Cornell University, Ithaca, 1973
  11. J.S.R. Jang, C.T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing, Prentice Hall, 1997
  12. The IEEE Reliability Test System-1996, A report prepared by the Reliability Test System Task Force of the Application of Probability Methods Subcommittee, IEEE Transactions on Power Systems, Vol. 14, Issue 3, 1999

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