DocumentCode :
175901
Title :
Study on EV charging station location planning based on the load balance principle with agent-based AnyLogic simulation
Author :
Ruifeng Shi ; Shiyao Zheng ; Chaoqun Zhang ; Li Zhang
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
fYear :
2014
fDate :
May 31 2014-June 2 2014
Firstpage :
1515
Lastpage :
1519
Abstract :
Electrification of the transportation sector is gradually becoming a global trend due to the environmental benefits of electric vehicles (EV), which not only helps to reduce greenhouse gas emissions, but also helps to reduce the burden of fossil fuel resources need. In order to analyze and evaluate the performance of different EV charging station location schemes, a pre-built AnyLogic Urban Dynamics model with considering population, business, housing, and transport infrastructure is employed to simulate the private EV electricity demand per hour in this paper. Furthermore, two typical EV charging station location schemes for Beijing City´s urban area is adopted to illustrate the performance difference between these models, in which the plan A showed a serious load unbalance problem by contrast to the plan B, which further demonstrates the value of our simulation model on helping the decision maker with such issues. We can find that the optimal EV charging station will avoid the waste of resource and meet the charging requirement.
Keywords :
digital simulation; electric vehicles; environmental factors; town and country planning; traffic engineering computing; Beijing city urban area; EV charging station location planning; agent-based AnyLogic simulation; electric vehicles; environmental benefits; fossil fuel resources; greenhouse gas emissions; load balance principle; prebuilt AnyLogic urban dynamics model; private EV electricity demand; transportation sector electrification; Charging stations; Computational modeling; Electric vehicles; Load modeling; Mathematical model; Vehicle dynamics; Agent-based modeling; AnyLogic; Charging station location planning; Electric vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
Type :
conf
DOI :
10.1109/CCDC.2014.6852407
Filename :
6852407
Link To Document :
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