DocumentCode
326529
Title
Determination of local transient stability control based on neural networks
Author
Yutian Liu ; Zhang, Peng ; Gao, Tao ; Xia, Daozhi
Author_Institution
Shandong Univ. of Technol., China
Volume
2
fYear
1998
fDate
3-5 Mar 1998
Firstpage
393
Abstract
In order to apply neural networks to practical power systems, two feature reduction methods are presented in this paper. One introduces the generator coherent clustering and electrical distance to reduce the number of features, and the other adopts a linear neural network to perform feature extraction and trains it together with all the sub-neural networks. Simulation results of the Northwest power system in China indicate the feasibility of local transient stability control decisions in large-scale power systems based on neural networks
Keywords
control system analysis; control system synthesis; feature extraction; large-scale systems; learning (artificial intelligence); neurocontrollers; power system control; power system stability; power system transients; China; control design; control simulation; electrical distance; feature extraction; feature reduction methods; generator coherent clustering; large-scale power systems; linear neural net training; local transient stability control; neural networks; sub-neural networks; Control systems; Feature extraction; Large-scale systems; Neural networks; Power generation; Power system simulation; Power system stability; Power system transients; Stability analysis; Transient analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on
Print_ISBN
0-7803-4495-2
Type
conf
DOI
10.1109/EMPD.1998.702584
Filename
702584
Link To Document