• DocumentCode
    2584865
  • Title

    Quickprop algorithm for transfer capability calculations

  • Author

    Luo, X. ; Patton, A.D. ; Singh, C.

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    31 Jan-4 Feb 1999
  • Firstpage
    890
  • Abstract
    The problem of real power transfer capability, under multi-area interchange schedules, is approached by a neural network solution methodology in this paper. Generator status, line status and load status serve as the inputs for the neural network and the output is the transfer capability as determined by OPF. The Quickprop algorithm, which is faster than the standard BP algorithm, is used to train the neural network. Having trained the neural network, the solution for a given power system condition can be determined very quickly. A case study is presented demonstrating the feasibility of this approach. The new method will be useful for reliability assessment in the new utility environment.
  • Keywords
    learning (artificial intelligence); load flow; power system analysis computing; power system interconnection; power transmission; Quickprop algorithm; generator status; line status; load status; multi-area interchange schedules; neural network solution methodology; neural network training; optimal power flow; reliability assessment; transfer capability calculations; Artificial neural networks; Load flow; Neural networks; Power system interconnection; Power system modeling; Power system reliability; Power system stability; Power transmission lines; Reactive power; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society 1999 Winter Meeting, IEEE
  • Print_ISBN
    0-7803-4893-1
  • Type

    conf

  • DOI
    10.1109/PESW.1999.747286
  • Filename
    747286