By Topic

Dynamic reactive power optimization using mathematical morphology and genetic 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
$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)
Anan Zhang ; School of Electrical Engineering & Information, Sichuan University, Chengdu 610065, Sichuan Province, China ; Zhenchao Jiang ; Honggeng Yang

A new approach of dynamic reactive power optimization is presented in this paper, which is based on mathematical morphology and genetic algorithm. Due to the difficulty of controlling the compensatorpsilas operation-time-number, a mathematical morphology filter is used to transfer the problem into filtering alternative images consisting of alleles on chromosomes. At the same time, some improvements are made in crossover and mutation for accelerating the speed of genetic algorithm, in which the genetic character is introduced to avoid breaking the excellent combination of genes and according to the correction of particle velocity derived from particle swarm optimization, an evolutional mutation based on excellent genetic character is presented. The practice in a distribution network proves that the algorithm presented in this paper is right and effective.

Published in:

Industrial Technology, 2008. ICIT 2008. IEEE International Conference on

Date of Conference:

21-24 April 2008