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
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