Title :
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
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;
Conference_Titel :
Advanced Power System Automation and Protection (APAP), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-9622-8
DOI :
10.1109/APAP.2011.6180686
