• DocumentCode
    822039
  • Title

    Probabilistic power system production cost and reliability calculation by the Z-transform method

  • Author

    Sutanto, D. ; Outhred, H.R. ; Lee, Y.B.

  • Author_Institution
    New South Wales Univ., Kensington, NSW, Australia
  • Volume
    4
  • Issue
    4
  • fYear
    1989
  • fDate
    12/1/1989 12:00:00 AM
  • Firstpage
    559
  • Lastpage
    566
  • Abstract
    The authors describe a novel method of probabilistic power system production cost and reliability calculation using the Z transform. In the proposed method, the generating unit available capacity probability density functions (PDFs) are represented by probability impulses. These PDFs are convolved using the Z transform to produce equivalent capacity PDFs. By operating the equivalent capacity PDFs on the system demand, the unit energies, loss of load probability (LOLP), and expected unserved energy (EUE) can be calculated for each load level and the total demand. The method is compared with the cumulant method and Calebrese´s traditional direct convolution procedure in terms of accuracy and computing time using the IEEE Reliability Test System. The main advantage of the new method is that actual load and generator availability data can be used directly, rather than via a mathematical representation such as cumulants. An efficient recursive algorithm using the Z transform procedure has been formulated to allow fast evaluations of convolution and deconvolution of PDFs. In terms of computing time, the new method is not much slower than the cumulant method. LOLP and EUE are also calculated more accurately
  • Keywords
    power systems; probability; reliability; EUE; IEEE Reliability Test System; LOLP; Z-transform method; available capacity probability density functions; expected unserved energy; loss of load probability; probabilistic power system production cost; probability impulses; recursive algorithm; reliability calculation; Australia; Capacity planning; Convolution; Costs; Power generation; Power system reliability; Power system simulation; Probability density function; Probability distribution; Production systems;
  • fLanguage
    English
  • Journal_Title
    Energy Conversion, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8969
  • Type

    jour

  • DOI
    10.1109/60.41714
  • Filename
    41714