DocumentCode
2327869
Title
Transient stability study using artificial neural networks models of generator, excitation system, governor
Author
Qian, Ai ; Shande, Shen ; Shouzhen, Zhu
Author_Institution
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume
2
fYear
1998
fDate
18-21 Aug 1998
Firstpage
1331
Abstract
In this paper, the power system models established by artificial neural networks (ANNs) including generator, excitation system and governor are presented. Meanwhile, the three parts of the generation unit are connected together as a detail model. Furthermore, the detail model is written into power system network equations and the power system transient process is calculated using them. The calculation results demonstrate that artificial neural network models can give a precise description of a generator´s transient processes
Keywords
control system analysis computing; electric generators; electric machine analysis computing; exciters; machine theory; neural nets; power system analysis computing; power system transient stability; artificial neural networks; computer simulation; excitation system; generator; governor; network equations; power system models; power system transient process; Artificial neural networks; Character generation; Equations; Neurons; Power generation; Power system analysis computing; Power system modeling; Power system stability; Power system transients; Recurrent neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location
Beijing
Print_ISBN
0-7803-4754-4
Type
conf
DOI
10.1109/ICPST.1998.729302
Filename
729302
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