• DocumentCode
    3583948
  • Title

    Electricity market strategy characterisation with fuzzy logic: application to different types of power plants

  • Author

    Massucco, S. ; Meini, L. ; Silvestro, F. ; Burt, G. ; Galloway, S. ; McDonald, J. ; Siewierski, T.

  • Author_Institution
    Dept. of Electr. Eng., Genoa Univ., Italy
  • fYear
    2004
  • Firstpage
    356
  • Lastpage
    361
  • Abstract
    In the last decade many countries have gone through liberalisation of their electricity industries. In many instances this has seen a move towards increased competition with market forces left to determine price. The resultant changes to market structure affect both electricity market participation and the operation of the power systems requiring a whole range of new issues to be addressed. This paper proposes an electricity market oriented tool that creates bidding strategies in a competitive market environment by combining fuzzy logic and deterministic approaches. In this way the technical, economic and behavioural decision making process of a generation based market participant is considered. The proposed model can be accommodated by both a power exchange and a balancing market The results obtained for different types of plants have been compared with actual market results for a representative combined cycle gas turbine plant (CCGT).
  • Keywords
    combined cycle power stations; decision making; fuzzy logic; gas turbine power stations; power generation economics; power markets; power plants; bidding strategy; combined cycle gas turbine plant; competitive markets; economic decision making; electricity industry liberalisation; electricity market; fuzzy logic; power exchange; power generation; power plants; price determination; Decision making; Electricity supply industry; Environmental economics; Fuzzy logic; Power generation; Power generation economics; Power markets; Power system economics; Power systems; Turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems, 2004 International Conference on
  • Print_ISBN
    0-9761319-1-9
  • Type

    conf

  • Filename
    1378714