• DocumentCode
    1065958
  • Title

    Probability models for estimating the probabilities of cascading outages in high-voltage transmission network

  • Author

    Chen, Qiming ; Jiang, Chuanwen ; Qiu, Wenzheng ; McCalley, James D.

  • Author_Institution
    PJM Interconnection, ValleyForge, PA
  • Volume
    21
  • Issue
    3
  • fYear
    2006
  • Firstpage
    1423
  • Lastpage
    1431
  • Abstract
    This paper discusses a number of probability models for multiple transmission line outages in power systems, including generalized Poisson model, negative binomial model, and exponentially accelerated model. These models are applied to the multiple transmission outage data for a 20-year period for North America. The probabilities of the propagation of transmission cascading outage are calculated. These probability magnitudes can serve as indexes for long-term planning and can also be used in short-term operational defense to such events. Results from our research show that all three models apparently explain the occurrence probability of higher order outages very well. However, the exponentially accelerated model fits the observed data and predicts the acceleration trends best. Strict chi-squared fitness tests were done to compare the fitness among these three models, and the test results are consistent with what we observe
  • Keywords
    Poisson equation; power transmission planning; probability; cascading outages; chi-squared fitness tests; generalized Poisson model; high-voltage transmission network; long-term planning; negative binomial model; occurrence probability; probability estimation; transmission outage; Acceleration; Costs; Intelligent networks; Power system analysis computing; Power system modeling; Power system planning; Power transmission lines; Predictive models; Probability; Testing; Blackouts; cascading; exponentially accelerated cascading (EAC); generalized Poisson distribution (GPD); high-order contingency; multiple transmission outages; negative binomial distribution; power law; rare events;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2006.879249
  • Filename
    1664980