DocumentCode :
2838621
Title :
Estimation of closest saddle node bifurcation using ANN based analog simulation
Author :
Joshi, S.K. ; Srivastava, S.C.
Author_Institution :
Dept. of Electr. Eng., M.S. Univ. of Baroda, Vadodara, India
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
503
Abstract :
With growing interconnections along with economic and environmental pressures, the possible threat of voltage instability is becoming increasingly pronounced in the power system network. Due to increased use of compensating devices, voltage alone has become a poor indicator of voltage stability. Hence, voltage stability margin or distance to voltage instability point should be considered along with the bus voltage deviation values for contingency selection. In this paper, a novel method employing an analog simulation based neural network, to enhance the speed for determining stability margin for contingency selection, has been suggested
Keywords :
analogue simulation; bifurcation; neural nets; nonlinear programming; power system dynamic stability; power system interconnection; power system security; power system simulation; ANN based analog simulation; analog simulation based neural network; bus voltage deviation; closest saddle node bifurcation estimation; compensating devices; contingency selection; distance to voltage instability point; economic pressures; environmental pressures; nonlinear programming; power system interconnection; voltage instability; voltage stability; voltage stability margin; Artificial neural networks; Bifurcation; Economic indicators; Environmental economics; Neural networks; Power generation economics; Power system economics; Power system interconnection; Power system stability; Voltage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-6338-8
Type :
conf
DOI :
10.1109/ICPST.2000.900108
Filename :
900108
Link To Document :
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