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

Author

Yue Kai-wei ; Zhou Yu-Hui ; Cheng Chao ; Yang Jiang ; He Zhan-yong ; Liang Na

Author_Institution

Grad. Sch. of Electr. Eng., Beijing Jiaotong Univ., Beijing, China

Volume

3

fYear

2011

Firstpage

2036

Lastpage

2039

Abstract

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.

Keywords

distributed power generation; genetic algorithms; nonlinear programming; power engineering computing; radial basis function networks; smart power grids; RBF neural networks; accelerating genetic algorithms; artificial neural network; distributed generation access; distributed power grid; energy storage system; nonlinear optimization problems; smart grid power quality assessment; Reliability; Smart grids; Voltage fluctuations; accelerating genetic algorithms; artificial neural networks; power quality; smart grid;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Beijing

Print_ISBN

978-1-4244-9622-8

Type

conf

DOI

10.1109/APAP.2011.6180686

Filename

6180686