• DocumentCode
    1196189
  • Title

    Tuning of discretization in bimatrix game approach to power system market analysis

  • Author

    Lee, Kwang-Ho ; Baldick, Ross

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Dankook Univ., Seoul, South Korea
  • Volume
    18
  • Issue
    2
  • fYear
    2003
  • fDate
    5/1/2003 12:00:00 AM
  • Firstpage
    830
  • Lastpage
    836
  • Abstract
    An important aspect of the study of power system markets involves the assessment of strategic behavior of participants maximizing their profits. In models of imperfect competition of a deregulated electricity system, the key task is to find the Nash equilibrium. In this paper, the bimatrix approach for finding Nash equilibria in electricity markets is investigated. This approach determines pure and mixed equilibria using the complementary pivot algorithm. The mixed equilibrium in the matrix approach has the equal number of nonzeros property. This property makes it difficult to reproduce a smooth continuous distribution for the mixed equilibrium. This paper proposes an algorithm for adjusting the quantization value of discretization to reconstruct a continuous distribution from a discrete one.
  • Keywords
    game theory; power markets; power systems; Nash equilibrium; bimatrix approach; bimatrix game approach; complementary pivot algorithm; continuous distribution reconstruction; deregulated electricity system; discretization tuning; imperfect competition; matrix approach; mixed equilibria; mixed equilibrium; nonzeros property; power system market analysis; profits maximisation; pure equilibria; quantization value; smooth continuous distribution; strategic behavior assessment; Algorithm design and analysis; Electricity supply industry; Electricity supply industry deregulation; Mathematical programming; Nash equilibrium; Oligopoly; Power industry; Power system analysis computing; Power system modeling; Quantization;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2002.807067
  • Filename
    1198320