• DocumentCode
    2837809
  • Title

    Computing Optimum Bidding Strategy of Gencos Using Simulated Annealing Method

  • Author

    Soleymani, S. ; Ranjbar, A.M. ; Shirani, A.R. ; Sadati, N.

  • Author_Institution
    Sharif Univ. of Technol., Tehran
  • fYear
    2006
  • fDate
    15-17 Dec. 2006
  • Firstpage
    2563
  • Lastpage
    2568
  • Abstract
    This paper describes a new method that uses simulated annealing (SA) method for analyzing the competition among Generating Companies (Gencos) where they have incomplete information about their opponents. Each Genco models its opponents with their generating cost coefficients. The proposed methodology employs the supply function equilibrium (SFE) for modeling a Genco´s bidding strategy. Gencos change their bidding strategies until Nash equilibrium points are obtained. Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging up-to-date. This paper uses SA to compute Nash equilibria strategies of Gencos and then the obtained results are compared with another computational intelligence technique (Genetic Algorithm) and a mathematical method (GAMS/DICOPT).
  • Keywords
    game theory; power markets; simulated annealing; Gencos; Generating Companies; Nash equilibrium; energy market; finite strategic game; optimum bidding strategy; simulated annealing method; supply function equilibrium; Analytical models; Computational modeling; Costs; Electricity supply industry; Fuels; Game theory; Nash equilibrium; Power generation; Power system modeling; Simulated annealing; Deregulation; Energy Market; Nash Equilibrium Point; Optimal Bidding Strategy; Simulated Annealing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
  • Conference_Location
    Mumbai
  • Print_ISBN
    1-4244-0726-5
  • Electronic_ISBN
    1-4244-0726-5
  • Type

    conf

  • DOI
    10.1109/ICIT.2006.372604
  • Filename
    4237926