Title :
Online risk-based security assessment
Author :
Ni, Ming ; McCalley, James D. ; Vittal, Vijay ; Tayyib, Tayyib
Author_Institution :
Iowa State Univ., Ames, IA, USA
fDate :
2/1/2003 12:00:00 AM
Abstract :
The work described in this paper was motivated by a perceived increase in the frequency at which power system operators are encountering high stress in bulk transmission systems and the corresponding need to improve security monitoring of these networks. Online risk-based security assessment provides rapid online quantification of a security level associated with an existing or forecasted operating condition. One major advantage of this approach over deterministic online security assessment is that it condenses contingency likelihood and severity into indices that reflect probabilistic risk. Use of these indices in control room decision making leads to increased understanding of potential network problems, including overload, cascading overload, low voltages, and voltage instability, resulting in improved security-related decision making. Test results on large-scale transmission models retrieved from the energy-management system of a U.S. utility company are described.
Keywords :
control system analysis; power system security; power system stability; power transmission control; probability; risk management; USA; bulk transmission system stress; cascading overload; contingency likelihood; contingency severity; energy-management system; low voltages; online risk-based security assessment; overload; probabilistic risk; voltage instability; Decision making; Frequency; Information security; Large-scale systems; Low voltage; Medical services; Power system modeling; Power system security; Uncertainty; Voltage control;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2002.807091