DocumentCode :
1811839
Title :
Neural-net-based nonlinear control for prevention of voltage collapse
Author :
Chen, D. ; Mohler, R. ; Shahrestani, S.A. ; Hill, D.J.
Author_Institution :
Siemens Power Syst. Control, Brooklyn Park, MN, USA
Volume :
3
fYear :
1999
fDate :
1999
Firstpage :
2156
Abstract :
In this paper, power system stability is addressed which includes the regular, generator-angle, transient stability and load-driven voltage instability. Flexible ac transmission systems (FACTS) devices are utilized for improvement of power transfer capability as well as enhancement of power system stability. Techniques are developed for synthesis of nonlinear neural controllers to deal with the situation where generator dynamics and load dynamics are interlinked so that voltage instability or even voltage collapse is more likely to occur. The simulations illustrate the performance of the synthesized neural controllers. The techniques developed can be readily generalized to more general nonlinear power systems
Keywords :
flexible AC transmission systems; neurocontrollers; nonlinear control systems; power system stability; flexible ac transmission systems; generator dynamics; generator-angle; load dynamics; neural-net-based nonlinear control; nonlinear power systems; performance; power system stability; transient stability; voltage instability; Nonlinear dynamical systems; Power generation; Power system control; Power system dynamics; Power system modeling; Power system simulation; Power system stability; Power system transients; Power systems; Voltage control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Conference_Location :
Phoenix, AZ
ISSN :
0191-2216
Print_ISBN :
0-7803-5250-5
Type :
conf
DOI :
10.1109/CDC.1999.831239
Filename :
831239
Link To Document :
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