By Topic

Optimal design of SSSC damping controller to improve power system dynamic stability using modified intelligent algorithms

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)
Khani, S. ; Faculty of Electrical and Computer Engineering, University of Tabriz, 29 Bahman Boulevard, Iran ; Sadeghi, M. ; Hosseini, S.H.

In this paper, A modified intelligent Particle Swarm Optimization (PSO) and continuous Genetic Algorithms (GA) have been used for optimal selection of the static synchronous series compensator (SSSC) damping controller parameters in order to improve power system dynamic response and its stability. Then the performance of these methods on system stability has been compared. First intelligent PSO and genetic algorithms are used to select the effective feedback signal of the damping controller and then simulation results are presented to compare the performance of the proposed SSSC controller in damping the critical modes in a Single-Machine Infinite-Bus SMIB power system. The comparison shows that PSO can reach faster than genetic algorithm to optimal selection of the static synchronous series compensator (SSSC) damping controller parameters and has better performance in damping oscillations.

Published in:

Power Electronic & Drive Systems & Technologies Conference (PEDSTC), 2010 1st

Date of Conference:

17-18 Feb. 2010