DocumentCode :
3450462
Title :
An improved particle swarm optimization for reactive power optimization
Author :
Qu Nana ; Ma Lixin ; Shan Guanhua ; Ren Youming
Author_Institution :
Dept. of Electr. Eng., Univ. of Shanghai for Sci.& Tech., Shanghai, China
Volume :
2
fYear :
2011
fDate :
20-22 Aug. 2011
Firstpage :
362
Lastpage :
365
Abstract :
Reactive power optimization (RPO) is a complex combinatorial programming problem that reduces power losses and improve voltage profiles in a power system. In this paper, RPO is solved by using particle swarm optimization (PSO), while one problem exists in standard PSO is its tendency of trapping into local optima. To overcome this drawback, an improved particle swarm optimization with Cauchy mutation (IPSO) is proposed and applied in RPO on IEEE-14 bus, the comparison of the result of several different methods shows that the IPSO can more effectively solve the reactive power optimization problem in power system.
Keywords :
particle swarm optimisation; power engineering computing; power system simulation; reactive power; Cauchy mutation; complex combinatorial programming problem; particle swarm optimization; reactive power optimization; Convergence; Generators; Optimization; Particle swarm optimization; Reactive power; Voltage control; Cauchy particle swarm optimization; power system; reactive power optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Technology and Artificial Intelligence Conference (ITAIC), 2011 6th IEEE Joint International
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-8622-9
Type :
conf
DOI :
10.1109/ITAIC.2011.6030350
Filename :
6030350
Link To Document :
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