DocumentCode :
3395823
Title :
Development of an Improved Particle Swarm Optimization Algorithm and Its Application in the Optimal Design of Nuclear Power System
Author :
Liu, Chengyang ; Yan, Changqi
Author_Institution :
Nat. Defense Key Discipline Lab. of Nucl. Safety & Simulation Technol., Harbin, China
fYear :
2012
fDate :
27-29 March 2012
Firstpage :
1
Lastpage :
4
Abstract :
This article focuses on the development of an improved particle swarm optimization algorithm and its application in the optimal design of the nuclear power system, whose goal is to find a combination of system parameter values that minimize the weight of the system given the power capacity requirement and safety criteria. An improved particle swarm optimization (IPSO) algorithm was developed using the feasibility rule constraints handling method, crossover and mutation operator. Using the improved compound shape algorithm to do the local search after the particle swarm reaches a satisfactory point. The algorithm gave satisfactory optimization results from both search efficiency and accuracy perspectives. This IPSO successfully solved the design optimization problem of nuclear power system. It is an advanced and efficient methodology that can be applied to the similar optimization problems in other areas.
Keywords :
constraint handling; electrical safety; nuclear power stations; particle swarm optimisation; IPSO algorithm; crossover operator; feasibility rule constraint handling method; improved compound shape algorithm; improved particle swarm optimization algorithm; mutation operator; nuclear power system; optimal design; power capacity requirement; safety criteria; Algorithm design and analysis; Generators; Inductors; Optimization; Particle swarm optimization; Power systems; Safety;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
ISSN :
2157-4839
Print_ISBN :
978-1-4577-0545-8
Type :
conf
DOI :
10.1109/APPEEC.2012.6307492
Filename :
6307492
Link To Document :
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