By Topic

Power System Reactive Power Optimization Based on Adaptive Particle Swarm Optimization Algorithm

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

4 Author(s)
Yang Li ; Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang ; Liqun Gao ; Junzheng Zhang ; Yang Li

Aiming at the precocious convergence problem of particle swarm optimization algorithm, adaptive particle swarm optimization (APSO) algorithm was presented. In this algorithm, inertia weight was nonlinearly adjusted by using population diversity information. Velocity mutation operator and position crossover operator were both introduced and the global performance was clearly improved. The algorithm had been applied to reactive power optimization. The simulation results of the standard IEEE-30-bus power system had indicated that APSO was able to undertake global search with a fast convergence rate and a feature of robust computation. It was proved to be efficient and practical during the reactive power optimization

Published in:

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on  (Volume:2 )

Date of Conference:

0-0 0