• DocumentCode
    2564281
  • Title

    The optimal bidding models for power energy producer based on Static Bayesian Game theory

  • Author

    Jianchao, Hou ; Zhong-fu, Tan ; Mian-Bin, Wang ; Haiyang, Jiang

  • Author_Institution
    Inst. of Electr. Econ., North China Electr. Power Univ., Beijing
  • fYear
    2008
  • fDate
    2-4 July 2008
  • Firstpage
    3123
  • Lastpage
    3128
  • Abstract
    With the increasingly perfect power market in China, competitive generation bidding based on contracts for differences has become a inevitable direction. Independent generator, as one of market competition participants, will operate with a goal of maximizing benefits and care for optimal bidding strategy considering contracts for differences. Based on power grid company pursuing minimum purchasing electricity charges, the paper constructs relationship matrix between the generation amount, bidding and the rivalpsilas, then with static Bayesian game theory establishes the optimal bidding model considering contracts for differences. By solving the model, the Bayesian Nash equilibrium of the bidding and power generation amount in system may be confirmed. Example shows the model is feasible, and it is useful for power producerpsilas decision.
  • Keywords
    Bayes methods; contracts; decision theory; game theory; power grids; power markets; Bayesian Nash equilibrium; China; competitive generation bidding; contracts; minimum purchasing electricity charges; optimal bidding model; power energy producer; power grid company; power market; relationship matrix; static Bayesian game theory; Bayesian methods; Costs; Game theory; Production; Bidding; Contracts for Differences; Non-cooperative Game; Power Producer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2008. CCDC 2008. Chinese
  • Conference_Location
    Yantai, Shandong
  • Print_ISBN
    978-1-4244-1733-9
  • Electronic_ISBN
    978-1-4244-1734-6
  • Type

    conf

  • DOI
    10.1109/CCDC.2008.4597901
  • Filename
    4597901