• DocumentCode
    3252936
  • Title

    Classification of input and output variables for a Bayesian model to analyze animal-related outages in overhead distribution systems

  • Author

    Gui, Min ; Pahwa, Anil ; Das, Sanjoy

  • Author_Institution
    Quanta Technol., LLC, Raleigh, NC, USA
  • fYear
    2010
  • fDate
    14-17 June 2010
  • Firstpage
    469
  • Lastpage
    474
  • Abstract
    Animals, such as squirrels, cause significant outages in overhead distribution systems. Models that would accurately estimate outages caused by animals would be very useful for utilities for year-end analysis of reliability performance of the distribution system. Large increase in outages caused by animals would require the utility to do further evaluation and take remedial actions. A two-layer Bayesian network model with Month-Type, Level of Fair Weather Days in the week, and Outage Level in the previous week as input and Outage Level in the week is presented in this paper for estimation of weekly animal-related outages. Results of different approaches for classification of inputs and output are presented, which are then compared to select the best classification of input and output variables for the model.
  • Keywords
    Bayes methods; power distribution reliability; Bayesian model; animal-related outages; distribution system reliability; overhead distribution systems; Animals; Bayesian methods; Distributed computing; Graphical models; Input variables; Neural networks; Performance analysis; Reliability engineering; Temperature; Wavelet analysis; Bayesian model; animal-related outage; distribution system; distribution system reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Probabilistic Methods Applied to Power Systems (PMAPS), 2010 IEEE 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-5720-5
  • Type

    conf

  • DOI
    10.1109/PMAPS.2010.5528968
  • Filename
    5528968