Title :
On-line dynamic security contingency screening using artificial neural networks
Author :
Chan, K.W. ; Edwards, A.R. ; Dunn, R.W. ; Daniels, A.R.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., China
fDate :
11/1/2000 12:00:00 AM
Abstract :
On-line dynamic security analysis has now become realistic due to advances in computer technology and algorithms for security assessment. Details of pattern recognition based electromechanical stability screens which have been implemented within a dynamic security assessor are presented. Use of statistical functions of features is shown to overcome the dimensionality problem of applying pattern recognition techniques to large power systems. The low computational cost of this approach coupled with efficient operation has resulted in a significant step towards achieving full online dynamic security assessment
Keywords :
neural nets; pattern recognition; power system analysis computing; power system security; power system stability; artificial neural networks; dynamic security assessor; electromechanical stability screens; low computational cost; on-line dynamic security contingency screening; online dynamic security assessment; pattern recognition; statistical functions;
Journal_Title :
Generation, Transmission and Distribution, IEE Proceedings-
DOI :
10.1049/ip-gtd:20000712