DocumentCode
570296
Title
Optimal Planning of charging station for electric vehicle based on particle swarm optimization
Author
Liu Zi-fa ; Zhang Wei ; Ji Xing ; Li Ke
Author_Institution
Sch. of Electr. & Electron. Eng., North China Electr. Power Univ., Beijing, China
fYear
2012
fDate
21-24 May 2012
Firstpage
1
Lastpage
5
Abstract
How to determine location and scale of electric vehicle charging station is a new problem for many researchers. A comprehensive objective function considering geographic information, construction cost and running cost is built in this paper. In objective function, construction cost consists of land cost, and investment in distribution transformer. Running cost includes power supply losses and with traffic flow as constraint conditions, which scientifically and comprehensively reflects the substance problem of locating and sizing of electric vehicle charging station. Electric vehicle charging station locating and sizing is a non-convex, nonlinear, and combinatorial optimization problem. On the basis of the established objective function, an adaptive particle swarm optimization (APSO) algorithm is proposed to solve the problem in this paper. The proposed algorithm and optimization model are tested by a planning example of charging station for electric vehicle to verify the feasibility and effectiveness.
Keywords
battery powered vehicles; particle swarm optimisation; planning; road traffic; APSO algorithm; adaptive particle swarm optimization algorithm; combinatorial optimization problem; comprehensive objective function; construction cost; distribution transformer; electric vehicle charging station; geographic information; nonconvex optimization problem; nonlinear optimization problem; optimal planning; power supply losses; running cost; traffic flow; Batteries; Educational institutions; Electric vehicles; Mathematical model; Particle swarm optimization; Planning; Power systems; APSO; charging station; electric vehicle; traffic flow;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Smart Grid Technologies - Asia (ISGT Asia), 2012 IEEE
Conference_Location
Tianjin
Print_ISBN
978-1-4673-1221-9
Type
conf
DOI
10.1109/ISGT-Asia.2012.6303112
Filename
6303112
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