An agent-based electric vehicle ecosystem model: San Francisco case study

被引：48
|
作者：
Adepetu, Adedamola [1 ]
Keshav, Srinivasan [1 ]
Arya, Vijay [2 ]
机构：
[1] Univ Waterloo, Cheriton Sch Comp Sci, Waterloo, ON N2L 3G1, Canada
[2] IBM Res, Block G2,Manyata Embassy Business Pk,Outer Ring R, Bangalore 560045, Karnataka, India
来源：
TRANSPORT POLICY | 2016年 / 46卷
关键词：
Agent-based modeling; Electric vehicle; Electric vehicle adoption; PLUG-IN HYBRID; DEMAND;
D O I：
10.1016/j.tranpol.2015.11.012
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
The widespread commercial availability of plug-in electric vehicles (EVs) in recent years motivates policies to encourage EV adoption and infrastructure to cope with the increasing number of EVs. We present an agent-based EV ecosystem model that incorporates EV adoption and usage with spatial and temporal considerations and that can aid different EV industry stakeholders such as policymakers, utility operators, charging station planners, and EV manufacturers. The model follows an ecological modeling approach, and is used to determine how different policies and battery technologies affect EV adoption, EV charging, and charging station activity. We choose model parameters to fit San Francisco as a test city and simulate different scenarios. The results provide insight on potential changes to the San Francisco EV ecosystem as a result of changes in rebates, availability of workplace charging, public awareness of lower EV operational costs, and denser EV batteries. We find that our results match those obtained using other approaches and that the compact geographical size of San Francisco and its relative wealth make it an ideal city for EV adoption. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：109 / 122
页数：14
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