By Topic

Research on smart grid power quality assessment based on RBF neural networks and accelerating genetic 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

6 Author(s)
Yue Kai-wei ; Grad. Sch. of Electr. Eng., Beijing Jiaotong Univ., Beijing, China ; Zhou Yu-Hui ; Cheng Chao ; Yang Jiang
more authors

Distributed generation access is one of the key technologies in building smart grid. This paper added distributed power grid and energy storage system connected to the grid two indicators to current power quality assessment indicators, making the object of evaluation more comprehensive and reasonable. For the comprehensive assessment of power quality, making the assessment results more objective and accurate, constructed artificial neural network model of comprehensive assessment of power quality; take accelerated genetic algorithm to solve nonlinear optimization problems, and achieved good results.

Published in:

Advanced Power System Automation and Protection (APAP), 2011 International Conference on  (Volume:3 )

Date of Conference:

16-20 Oct. 2011