• DocumentCode
    999226
  • Title

    Power System Risk Assessment and Control in a Multiobjective Framework

  • Author

    Xiao, Fei ; McCalley, James D.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Iowa State Univ., Ames, IA
  • Volume
    24
  • Issue
    1
  • fYear
    2009
  • Firstpage
    78
  • Lastpage
    85
  • Abstract
    Traditional online security assessment determines whether the system is secure or not, but how secure or insecure is not explicitly indicated. This paper develops probabilistic indices, risk, to assess real-time power system security level. Risk captures not only event likelihood, but also consequence. System security level associated with low voltage and overload can be optimally controlled, using the NSGA multiobjective optimization method. A security diagram is used to visualize operating conditions in a way that enables both risk-based and traditional deterministic views. An index for cascading overloads is used to evaluate the Pareto optimal solutions. This paper shows that the multiobjective approach results in less risky and less costly operating conditions, and it provides a practical algorithm for implementation. The IEEE 24-bus RTS-1996 system is analyzed to show that risk-based system security control results in lower risk, lower cost, and less exposure to cascading outages.
  • Keywords
    power system control; power system security; probability; multiobjective optimization; online security assessment; power system control; power system risk assessment; power system security; probabilistic indices; Decision making; evolutionary algorithm; nonlinear multiobjective optimization; reliability; risk; security;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2008.2004823
  • Filename
    4682627