Probabilistic security analysis using SOM and Monte Carlo simulation Conference Paper

abstract

• This paper proposes a new probabilistic method involving transient stability and voltage stability for power system security assessment by combining Monte Carlo simulation and self organizing map(SOM). This overcomes the problem of large amount of computation time required of Monte Carlo simulation. SOM learns to recognize groups of similar input vectors in such a way that neurons physically near each other in the neuron layer respond to similar input vectors. Data classification by SOM can reduce sampling data, which reduces computation time for reliability security index when using classified data. A ease study of the IEEE RTS is given to demonstrate the efficiency of this approach.

name of conference

• 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)

authors

• Singh, Chanan

published proceedings

• 2002 IEEE POWER ENGINEERING SOCIETY WINTER MEETING, VOLS 1 AND 2, CONFERENCE PROCEEDINGS

author list (cited authors)

• Kim, H. C., & Singh, C.

citation count

• 14

complete list of authors

• Kim, HC||Singh, C

publication date

• January 2002

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Ieee Rts System
• Monte Carlo Simulation
• Optimal Power Flow
• Power System Reliability
• Self Organizing Map
• Som - Monte Carlo Simulation

Digital Object Identifier (DOI)

• 10.1109/pesw.2002.985107

International Standard Book Number (ISBN) 10

• 0-7803-7322-7

start page

• 755

end page

• 760

volume

• 2

URL

• http://dx.doi.org/10.1109/pesw.2002.985107