• DocumentCode
    3470920
  • Title

    Neural network based stochastic load flow analysis

  • Author

    Jain, Amit ; Tripathy, S.C. ; Balasubramanian, R. ; Grag, K. ; Kawazoe, Yoshyuki

  • Author_Institution
    Inst. for Mater. Res., Tohoku Univ., Sendai, Japan
  • Volume
    2
  • fYear
    2004
  • fDate
    21-24 Nov. 2004
  • Firstpage
    1845
  • Abstract
    Neural network based method for the analysis of stochastic load flow is presented in this paper. Stochastic load flow is a method for calculation of the effects of inaccuracies in input data on all output quantities through the load flow calculations. This gives a range of values for each output quantity, which represent the operative condition of the system, to a high degree of probability. It is desirable to know the state of the power system, with consideration of input data accuracies, on instant-to-instant basis and present method of neural network application to stochastic load flow problem is an effort in that direction. The proposed neural network model has been tested on a sample power system and simulation results are presented.
  • Keywords
    backpropagation; load flow; neural nets; power system simulation; probability; stochastic processes; backpropagation; instant-to-instant basis method; neural network; power system simulation; probability; stochastic load flow analysis; Control systems; Load flow; Load flow analysis; Neural networks; Power system analysis computing; Power system modeling; Power system planning; Power system simulation; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 2004. PowerCon 2004. 2004 International Conference on
  • Print_ISBN
    0-7803-8610-8
  • Type

    conf

  • DOI
    10.1109/ICPST.2004.1460302
  • Filename
    1460302