Application of fuzzy c-means clustering to power system coherency identification

  • Authors:

  • Shu-Chen Wang;Pei-Hwa Huang;Chi-Jui Wu

  • Affiliations:

  • Department of Electrical Engineering, National Taiwan Ocean University, Keelung, Taiwan;Department of Electrical Engineering, National Taiwan Ocean University, Keelung, Taiwan;Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan

  • Venue:
  • MMACTEE'06 Proceedings of the 8th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering
  • Year:
  • 2006

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Abstract

This paper presents the application to the identification of coherent generators in a power system based on the fuzzy c-means clustering. In view of the conceptual appropriateness and computational simplicity, the fuzzy c-means give a fast and flexible method for clustering analysis. At first, the coherency measures are derived from the time-domain responses of generators to reveal the relations between any pair of generators. Then the coherency measures are used as initial membership matrix in the fuzzy c-means clustering, which can let the clustering procedures converge quickly. An example power system is used to show the effectiveness of this method. The schemes of various number of generator clusters can be procured. The approach in this paper needs less iterative times and can directly begin a clustering procedure for any number of clusters.