• DocumentCode
    1030730
  • Title

    Transmission loss evaluation based on probabilistic power flow

  • Author

    Meliopoulos, A.P. ; Chao, X. ; Cokkinides, J. ; Monsalvatge, R.

  • Author_Institution
    Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    6
  • Issue
    1
  • fYear
    1991
  • fDate
    2/1/1991 12:00:00 AM
  • Firstpage
    364
  • Lastpage
    371
  • Abstract
    A simulation method for composite power systems is proposed for the purpose of evaluating the probability distribution function of transmission losses. The method accounts for the uncertainty of the electric load, availability of generating units, nonlinearities in the power flow equations, and major operating practices. The method is based on the following procedure. First, given the probabilistic electric load model, the probability distribution function of the power injection at generation buses is computed by taking into consideration the availability of generating units and economic dispatch practices. Next, transmission losses are expressed as a piecewise linear function of power injections at generation buses. Subsequently, the probability distribution function of transmission losses is computed. Validation of the method was performed via a Monte Carlo simulation. The method was applied to the 24-bus IEEE reliability test system, and the results are validated by comparing it to Monte Carlo simulation results
  • Keywords
    load flow; losses; power systems; probability; IEEE reliability test system; Monte Carlo simulation; composite power systems; economic dispatch practices; generating units; piecewise linear function; probabilistic power flow; probability distribution function; transmission loss evaluation; Availability; Distributed computing; Load flow; Load modeling; Nonlinear equations; Power generation; Power system simulation; Probability distribution; Propagation losses; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/59.131084
  • Filename
    131084