• DocumentCode
    586808
  • Title

    Comparison of four load models for reliability evaluation considering reconfiguration using Monte Carlo Simulation

  • Author

    Cho, Nam Ik ; Awodele, Kehinde

  • Author_Institution
    Dept. of Electr. Eng., Univ. of Cape Town, Rondebosch, South Africa
  • fYear
    2012
  • fDate
    Oct. 30 2012-Nov. 2 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents the reliability analysis of a distribution test system comparing four different load models using the time sequential Monte Carlo Simulation techniques. The load models investigated include: an average load, a time varying load, a five-step load and a beta probabilistic load model. The accuracy of representation of the actual customer load varies with different load models. The complexity and performance of the evaluation are also affected by the different approaches. Although the time varying and five-step load models provide adequate representation of the actual load, the probabilistic model using beta probability density function provides both adequate and adaptable representation. Useful information such as the distribution of the energy not supplied at each load point and for the whole system during failure events and an associated risk level are provided and can be used by power system planners for their decision-making process.
  • Keywords
    Monte Carlo methods; decision making; power system planning; power system reliability; probability; Monte Carlo simulation technique; decision-making process; distribution test system; energy distribution; load model; power system planners; probabilistic load model; probability density function; reliability analysis; reliability evaluation; Feeds; Load modeling; Reliability engineering; Load Modeling; Load Representation; Monte Carlo Simulation; Reconfiguration; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology (POWERCON), 2012 IEEE International Conference on
  • Conference_Location
    Auckland
  • Print_ISBN
    978-1-4673-2868-5
  • Type

    conf

  • DOI
    10.1109/PowerCon.2012.6401384
  • Filename
    6401384