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
Link To Document :
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