• DocumentCode
    713408
  • Title

    Energy bidding in a day-ahead electricity market using fuzzy optimization

  • Author

    Ijaz, Muhammad ; Sahito, Muhammad Faraz ; Al-Awami, Ali T.

  • Author_Institution
    Dept. of Electr. Eng., King Fahd Univ. of Pet. & Miner., Dhahran, Saudi Arabia
  • fYear
    2015
  • fDate
    17-19 March 2015
  • Firstpage
    2388
  • Lastpage
    2393
  • Abstract
    Optimal bidding is considered to be one of the most challenging task for energy producers to bid in a day ahead electricity market. The randomness and uncertain nature associated with the generation of stochastic resources further increase the complexity of the problem. In this paper, an optimal bidding strategy is developed for a Generation Company (GENCO) to participate in a day ahead electricity market, taking into account conventional and stochastic generation resources. GENCO tries to maximize the profit and minimize the risk associated with the uncertainty of stochastic generation and market price. An optimal bidding strategy is developed to participate in a day-ahead market to achieve GENCO owner maximized profit and reduced risk for the system operator. The problem is formulated as a fuzzy Mixed Integer Linear Programming (MILP).
  • Keywords
    fuzzy systems; integer programming; linear programming; power generation economics; power markets; tendering; GENCO; Generation Company; MILP; day-ahead electricity market; energy bidding; fuzzy mixed integer linear programming; fuzzy optimization; stochastic resources generation; Electricity supply industry; Generators; Optimization; Production; Schedules; Stochastic processes; Uncertainty; Day-Ahead Market; Energy Bidding; Fuzzy optimization; MILP; Market Price Forecast;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Technology (ICIT), 2015 IEEE International Conference on
  • Conference_Location
    Seville
  • Type

    conf

  • DOI
    10.1109/ICIT.2015.7125450
  • Filename
    7125450