• DocumentCode
    2592677
  • Title

    Clustering of Power System Data and Its Use in Load Pocket Identification

  • Author

    Rogers, Katherine M. ; Overbye, Thomas J.

  • Author_Institution
    Univ. of Illinois, Urbana, IL, USA
  • fYear
    2011
  • fDate
    4-7 Jan. 2011
  • Firstpage
    1
  • Lastpage
    10
  • Abstract
    When lines in a power system are constrained, the sensitivity of the power flows on these lines to generator output provides information about how the constraints divide the system and about the ability of sets of generators to increase revenue without increasing dispatch. Clustering is used to identify generators into groups with the potential for market advantage. In this paper, we discuss the implementation of several different clustering methods for identifying load pockets with potential market advantage.
  • Keywords
    electric generators; pattern clustering; power engineering computing; power system economics; generator output; load pocket identification; power system data clustering; Algorithm design and analysis; Approximation algorithms; Artificial neural networks; Clustering algorithms; Generators; Nearest neighbor searches; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Sciences (HICSS), 2011 44th Hawaii International Conference on
  • Conference_Location
    Kauai, HI
  • ISSN
    1530-1605
  • Print_ISBN
    978-1-4244-9618-1
  • Type

    conf

  • DOI
    10.1109/HICSS.2011.104
  • Filename
    5718674