• DocumentCode
    2395043
  • Title

    Coordination of bidding strategies in energy and spinning reserve markets for competitive suppliers using a genetic algorithm

  • Author

    Wen, Fushuan ; David, A.K.

  • Author_Institution
    Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, China
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    2174
  • Abstract
    The problem of building optimally coordinated bidding strategies for competitive suppliers in energy and spinning reserve markets is addressed. It is assumed that each supplier bids a linear energy supply function and a linear spinning reserve supply function into the energy and spinning reserve markets, respectively, and the two markets are dispatched separately to minimize customer payments. Each supplier chooses the coefficients in the linear energy and spinning reserve supply functions to maximize total benefits, subject to expectations about how rival suppliers will bid. A stochastic optimization model is first developed to describe this problem and a genetic algorithm based method is then presented to solve it. A numerical example is utilized to illustrate the essential features of the method
  • Keywords
    electricity supply industry; genetic algorithms; power system economics; stochastic processes; Monte Carlo method; ancillary service; competitive suppliers; customer payments minimisation; energy markets; genetic algorithm; linear energy supply function; linear spinning reserve supply function; optimally coordinated bidding strategies; spinning reserve markets; stochastic optimization model; total benefits maximisation; Automatic generation control; Economic forecasting; Electricity supply industry; Genetic algorithms; Job shop scheduling; Optimization methods; Power generation; Power generation economics; Spinning; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Summer Meeting, 2000. IEEE
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-6420-1
  • Type

    conf

  • DOI
    10.1109/PESS.2000.866983
  • Filename
    866983