• DocumentCode
    2396436
  • Title

    Modeling generation company decisions and electric market dynamics as discrete systems

  • Author

    Yang, Weiguo ; Sheblé, Gerald B.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Eng., Iowa State Univ., Ames, IA, USA
  • Volume
    3
  • fYear
    2002
  • fDate
    25-25 July 2002
  • Firstpage
    1385
  • Abstract
    Electric market dynamics (including quantity and price) is important to market design and reliability. Generation Companies (GENCOs) decision dynamics and interactions between them are the major source of market dynamics. This paper studies GENCOs decision dynamics as control problem and models electric market as control systems. Three kinds of GENCO decision-making processes are analyzed: probabilistic decision-making, learning effects during interactions with competitors, and a kind of complex decision-making. Based on these analyses, electric market is modeled respectively. Results shown this method can provide conclusions that are difficult or impossible to get by pure equilibrium analysis. The models can be used to study market properties, analyze interactions between GENCOs, and design control scheme.
  • Keywords
    decision making; electricity supply industry; power markets; power system economics; power system reliability; probability; competitor interactions; complex decision-making; decision dynamics; design control scheme; discrete systems; electric market dynamics; generation companies; generation company decisions; learning effects; market dynamics; market properties; power market design; power market reliability; probabilistic decision-making; Control system synthesis; Control theory; Decision making; Decision trees; Economic forecasting; Game theory; Power system dynamics; Power system modeling; Power system reliability; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Summer Meeting, 2002 IEEE
  • Conference_Location
    Chicago, IL, USA
  • Print_ISBN
    0-7803-7518-1
  • Type

    conf

  • DOI
    10.1109/PESS.2002.1043605
  • Filename
    1043605