• DocumentCode
    2133937
  • Title

    Bidding wind power in short-term electricity market based on multiple-objective fuzzy optimization

  • Author

    Xue, Yaosuo ; Venkatesh, Bala ; Chang, Liuchen

  • Author_Institution
    Dept. of Electr. & Comput. Eng., New Brunswick Univ., Fredericton, NB
  • fYear
    2008
  • fDate
    4-7 May 2008
  • Abstract
    Wind energy is promising with no fuel cost and zero greenhouse gas emissions; however, its intermittent and volatile nature has added much to operation burdens and thus a low penetration level in short-term or spot market. On the one hand, the power system operator is facing increased spinning reserve and generation uncertainty; on the other hand, the wind independent power producer (IPP) is subject to imbalance penalties in the balancing market. Previous literatures solely focused on maximizing the profit for a wind IPP formulating optimal bidding strategies without the consideration of operator side. This paper proposes a multiple-objective optimal bidding strategy to achieve both wind IPPpsilas maximum profit and less challenge for the operator. The strategy is formulated as a mixed-integer linear programming (MILP) problem with fuzzy optimization techniques. Analytic and numerical solutions will be given with discussion on risk control.
  • Keywords
    fuzzy set theory; linear programming; power generation economics; power markets; wind power plants; IPP; MILP; bidding wind power; mixed-integer linear programming; multiple-objective fuzzy optimization; numerical solutions; power system operator; risk control; short-term electricity market; spinning reserve; wind independent power producer; Costs; Electricity supply industry; Fuels; Global warming; Power generation; Power systems; Spinning; Uncertainty; Wind energy; Wind energy generation; Optimal bidding strategy; fuzzy optimization; mixed-integer linear programming; wind power;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical and Computer Engineering, 2008. CCECE 2008. Canadian Conference on
  • Conference_Location
    Niagara Falls, ON
  • ISSN
    0840-7789
  • Print_ISBN
    978-1-4244-1642-4
  • Electronic_ISBN
    0840-7789
  • Type

    conf

  • DOI
    10.1109/CCECE.2008.4564715
  • Filename
    4564715