• DocumentCode
    3110500
  • Title

    Study on bidding strategies of Gencos based on cumulative prospect theory and Bayesian learning model

  • Author

    Li, Chunjie ; Wu, Junyou ; Cheng, Yancong

  • Author_Institution
    North China Electr. Power Univ., Beijing, China
  • fYear
    2011
  • fDate
    26-28 March 2011
  • Firstpage
    958
  • Lastpage
    963
  • Abstract
    Because generators are limited rationality and their bidding strategies exist risk and uncertainty, this paper proposes a generators´ bidding model which is constructed by value function and weight function based on cumulative prospect theory. Value function shows the changes of losses and gains, and weight function reflects players´ psychological risk factors. The prospect value of bidding strategy is decided by value function and weight function, and the optimal bidding strategy is the biggest one among these prospect values. Finally, an example is employed, and the numerical results tell us that this method is feasible.
  • Keywords
    Bayes methods; commerce; higher order statistics; power markets; risk management; Bayesian learning model; Gencos; bidding strategy; cumulative prospect theory; psychological risk factor; value function; weight function; Bayesian methods; Biological system modeling; Electricity; Generators; Power systems; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Technology (ICIST), 2011 International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-9440-8
  • Type

    conf

  • DOI
    10.1109/ICIST.2011.5765132
  • Filename
    5765132