By Topic

Adaptive control for multi-machine power systems using genetic algorithm and neural network

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
$31 $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)
Senjyu, T. ; Dept. of Electr. & Electron. Eng., Ryukyus Univ., Okinawa, Japan ; Yamane, S. ; Uezato, K.

This paper presents an adaptive control technique for the variable series capacitor (VSrC) using a recurrent neural network (RNN). Since parameters of the controller determined by genetic algorithm (GA), which is one of the optimization algorithms, are optimum for only one operating point, it is possible not to realize good control performance against variations of the operating point and fault point. Then, the adaptive controller proposed in this paper consists of the optimum controller using GA and the recurrent neural network (RNN). As the RNN is learned on-line, robust control performance can be realized in various conditions. The effectiveness of this control method is verified by simulation results of a multi-machine power system

Published in:

Power Engineering Society Winter Meeting, 2000. IEEE  (Volume:2 )

Date of Conference: