• DocumentCode
    1240446
  • Title

    Development of probabilistic models for computing optimal distribution substation spare transformers

  • Author

    Chowdhury, Ali A. ; Koval, Don O.

  • Author_Institution
    MidAmerican Energy Co., Davenport, IA, USA
  • Volume
    41
  • Issue
    6
  • fYear
    2005
  • Firstpage
    1493
  • Lastpage
    1498
  • Abstract
    This paper presents probabilistic models developed based on the Poisson probability distribution for determining the optimal number of transformer spares for distribution transformer systems. The outage of a transformer is a random event and the probability mathematics can best describe this type of failure process. The developed models have been illustrated using illustrative 72-kV distribution transformer systems. Industry-average catastrophic transformer failure rate and a 1-year transformer repair or procurement time have been utilized in the examples considered in the paper. Among the models developed for determining the optimum number of transformer spares, the statistical economics model provides the best result as it attempts to minimize the total system cost including the cost of spares carried in the system.
  • Keywords
    Poisson distribution; distribution networks; electrical faults; maintenance engineering; probability; statistical analysis; transformer substations; 72 kV; Poisson probability distribution; cost minimization; industry-average catastrophic transformer failure; optimal distribution substation spare transformers; probabilistic mathematics; statistical economics; transformer repair; Distributed computing; Electrical equipment industry; Mathematics; Power generation economics; Power system modeling; Power system planning; Power system reliability; Probability distribution; Substations; Transformers; Catastrophic transformer failure; probability mathematics; reliability cost/reliability benefit; spare transformer; statistical economics;
  • fLanguage
    English
  • Journal_Title
    Industry Applications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0093-9994
  • Type

    jour

  • DOI
    10.1109/TIA.2005.858310
  • Filename
    1542301