• DocumentCode
    1144921
  • Title

    Reliability worth assessment of high-tech industry

  • Author

    Yin, Shih-An ; Chang, Rung-Fang ; Lu, Chan-Nan

  • Author_Institution
    Dept. of Electr. Eng., Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
  • Volume
    18
  • Issue
    1
  • fYear
    2003
  • fDate
    2/1/2003 12:00:00 AM
  • Firstpage
    359
  • Lastpage
    365
  • Abstract
    This paper introduces a new approach to customer interruption cost evaluation that recognizes the dispersed nature of the cost data. The proposed method is designated as the possibility distribution approach and provides a realistic and effective assessment of the losses incurred by high-tech industry electrical users due to power failures. Fuzzy linear regression models are used to describe the distribution and dispersed behaviors of interruption costs. Bootstrap technique is used to generate a sampling distribution of small samples so that confidence intervals of interruption costs of different high-tech sectors can be obtained. Using the obtained cost models, interruption costs and reliability worth of high-tech industries that require higher reliability and premium power service, can be properly assessed.
  • Keywords
    costing; industrial power systems; power system economics; power system faults; power system reliability; statistical analysis; bootstrap technique; confidence intervals; cost models; customer interruption cost evaluation; fuzzy linear regression models; high-tech industry reliability worth assessment; interruption costs; possibility distribution approach; power failures; sampling distribution; Cost function; Design methodology; Electricity supply industry; Energy consumption; Helium; Industrial economics; Linear regression; Power generation economics; Power system reliability; Sampling methods;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2002.807079
  • Filename
    1178820