By Topic

Neural-network-based intelligent control for improving dynamic performance of FACTS devices

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)
Wei Qiao ; Georgia Inst. of Technol., Atlanta ; Harley, R.G. ; Venayagamoorthy, G.K.

Flexible AC transmission system (FACTS) devices are widely recognized as powerful controllers to improve the dynamic performance and stability of power systems. The standard FACTS controllers are linear controllers designed around a specific operating point from a linearized system model with fixed parameters. However, at other operating points their performance degrades. Neural-network-based nonlinear intelligent control offers an attractive approach to overcome the drawbacks of the linear controllers. This paper presents two different neural-network-based intelligent control architectures, i.e., indirect adaptive neurocontrol and adaptive critic design based optimal neurocontrol, for designing the external control of an SSSC FACTS device. Simulation studies are carried out to evaluate the proposed nonlinear intelligent controllers on single machine infinite bus as well as multi-machine power systems. Results show that the proposed intelligent controls improve the dynamic performance of the SSSC and the associated power network.

Published in:

Bulk Power System Dynamics and Control - VII. Revitalizing Operational Reliability, 2007 iREP Symposium

Date of Conference:

19-24 Aug. 2007