DocumentCode
441631
Title
Investigation of Hybrid Genetic Algorithm/Particle Swarm Optimization Approach for the Power Flow Problem
Author
Ting, T.O. ; Wong, K.P. ; Chung, C.Y.
Author_Institution
Computational Intelligence Applications Research Laboratory (CIARLab), Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; E-MAIL: chan.xiuyan@polyu.edu.hk
Volume
1
fYear
2005
fDate
18-21 Aug. 2005
Firstpage
436
Lastpage
440
Abstract
This paper presents an investigation of possible hybrid genetic algorithm/particle swarm optimization approaches to evaluate the flow of electric power in power transmission network. The possible schemes are presented and their performances are illustrated by applying them to the power flow problem of the Klos Kerner 11-busbar system.
Keywords
Hybrid algorithms; Optimization; Power Flow; Genetic algorithms; Genetic mutations; Load flow; Nonlinear equations; Particle accelerators; Particle swarm optimization; Power system modeling; Power system stability; Power transmission; Steady-state; Hybrid algorithms; Optimization; Power Flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location
Guangzhou, China
Print_ISBN
0-7803-9091-1
Type
conf
DOI
10.1109/ICMLC.2005.1526986
Filename
1526986
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