DocumentCode
3187571
Title
Solved Environmental/Economic Dispatch Based on Multi-objective PSO
Author
Zhang, Libiao ; Xu, Xiangli ; Wang, Sujing ; Ma, Ming ; Zhou, Chunguang ; Sun, Caitang
Author_Institution
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
Volume
3
fYear
2010
fDate
11-12 May 2010
Firstpage
352
Lastpage
355
Abstract
A new multi-objective evolutionary algorithm for Environmental/Economic power Dispatch (EED) problem based on Particle Swarm Optimization (PSO) is proposed in this paper. The new algorithm has adopted the maintenance method of Pareto candidate solution set based on the max-min distance density. The algorithm effectively guarantees the convergence of the algorithm and the diversity solutions. The performance of algorithm has been examined over the standard IEEE 30-bus six-generator test system, and other multi-objective evolutionary algorithm are compared. Testing and comparing results showed this paper algorithm is feasible and efficient.
Keywords
evolutionary computation; particle swarm optimisation; power system economics; IEEE 30-bus six-generator test system; Pareto candidate solution set; environmental-economic power dispatch problem; max-min distance density; multiobjective PSO; multiobjective evolutionary algorithm; particle swarm optimization; Automation; Cost function; Educational institutions; Environmental economics; Evolutionary computation; Fuels; Particle swarm optimization; Power generation; Power generation economics; Power systems; Particle Swarm Optimization; environmental/economic dispatch; multiobjective evolutionary;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-7279-6
Electronic_ISBN
978-1-4244-7280-2
Type
conf
DOI
10.1109/ICICTA.2010.470
Filename
5522453
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