• DocumentCode
    2507693
  • Title

    Transmission loss allocation using Bayesian regularization backpropagation ANN

  • Author

    Choudhury, Nalin B Dev ; Goswami, Swapan K.

  • Author_Institution
    Electr. Eng. Dept., Nat. Inst. of Technolog Silchar, Silchar, India
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Allocating losses due to transmission in deregulated power market has become an important issue due to the changed operating mode of restructured power system. The difficulty with the job of loss allocation to the participating players lies in the fact that transmission losses have mutual couplings thus having no acceptable engineering solutions. Game theoretic approach might be an acceptable approach as they are developed based on the satisfaction of the individual players. Applying game theoretic approach on the other hand, as an independent solution tool is also difficult as it needs handling of huge data to solve a single case. A combination of the game theory and neural network thus is proposed here as an alternative solution.
  • Keywords
    game theory; neural nets; power engineering computing; power markets; power transmission; Bayesian regularization backpropagation ANN; game theoretic approach; power market deregulation; restructured power system; transmission loss allocation; Artificial neural networks; Bayesian methods; Game theory; Games; Propagation losses; Resource management; Training; Bayesian Regularization Backpropagation; Neural Network; Shapley value; Transmission loss allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2010 Annual IEEE
  • Conference_Location
    Kolkata
  • Print_ISBN
    978-1-4244-9072-1
  • Type

    conf

  • DOI
    10.1109/INDCON.2010.5712685
  • Filename
    5712685