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
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;
Conference_Titel :
Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4754-4
DOI :
10.1109/ICPST.1998.729302