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Dynamic security border identification using enhanced particle swarm optimization

delete2002-08-01
delete75
PRE
AI
I
I. Kassabalidis
M
M.A. El-Sharkawi
R
Robert J. Marks
L
L.S. Moulin
A
A.P. Alves da Silva
DOI:10.1109/TPWRS.2002.800942delete
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Abstract

Abstract

En 中文
The ongoing deregulation of the energy market increases the need to operate modern power systems close to the security border. This requires enhanced methods for the vulnerability border tracking. The high-dimensional nature of power systems' operating space makes this difficult. However, new multiagent search techniques such as particle swarm optimization have shown great promise in handling high-dimensional nonlinear problems. This paper investigates the use of a new variation of particle swarm optimization to identify points on the security border of the power system, thereby identifying a vulnerability margin metric for the operating point.
Keywords:
border tracking
particle swarm optimization
security assessment
system dynamics
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Journal

IEEE Transactions on Power Systems cover
IEEE Transactions on Power Systems
IF:
7.2
Papers:
1.1W
Citations:
5.0W

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