• DocumentCode
    2641076
  • Title

    Implication of different pricing rules on generators´ bidding behaviour

  • Author

    Sugianto, Ly-Fie ; Liao, Zhigang

  • Author_Institution
    Fac. of Bus. & Econ., Monash Univ., Clayton, VIC, Australia
  • fYear
    2011
  • fDate
    21-23 June 2011
  • Firstpage
    2421
  • Lastpage
    2425
  • Abstract
    This paper presents an agent-based model to examine the employment of different pricing rules, namely the Uniform pricing rule and Pay-as-bid pricing rule. Using Q-learning in repetitive trading process, generator agents learn the market characteristics and seek to maximize their revenue by exploring bidding strategies. Supply quantity withholding and generators´ collusion phenomenon have been observed in this study under certain market arrangements. The implication of different pricing rules on the total dispatch costs and generators´ profit are discussed in this paper.
  • Keywords
    learning (artificial intelligence); power markets; power system simulation; pricing; Q-learning; agent-based model; dispatch costs; generator profit; generators bidding behaviour; generators collusion phenomenon; pay-as-bid pricing rule; supply quantity withholding; uniform pricing rule; Conferences; Economics; Electricity; Electricity supply industry; Generators; ISO; Pricing; Q-Learning; agent-based model; auction market; pricing rules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
  • Conference_Location
    Beijing
  • ISSN
    pending
  • Print_ISBN
    978-1-4244-8754-7
  • Electronic_ISBN
    pending
  • Type

    conf

  • DOI
    10.1109/ICIEA.2011.5975999
  • Filename
    5975999