By Topic

Transient stability study using artificial neural networks models of generator, excitation system, governor

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ai Qian ; Dept. of Electr. Eng., Tsinghua Univ., Beijing, China ; Shen Shande ; Zhu Shouzhen

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

Published in:

Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on  (Volume:2 )

Date of Conference:

18-21 Aug 1998