TY - JOUR
T1 - The potential influence of cost-related factors on the adoption of electric vehicle
T2 - An integrated micro-simulation approach
AU - Zhuge, Chengxiang
AU - Wei, Binru
AU - Shao, Chunfu
AU - Dong, Chunjiao
AU - Meng, Meng
AU - Zhang, Jie
N1 - Funding Information:
This research was supported by the National Natural Science Foundation of China (Grant No. 51678044 ), the Fundamental Research Funds for the Central Universities (NO. 2017JBZ106 ), China, the Hong Kong Polytechnic University [ 1-BE2J ], and the ERC Starting Grant #678799 for the SILCI project (Social Influence and disruptive Low Carbon Innovation). We would also thank Dr. Mike Bithell for discussing with us about the development and application of the SelfSim-EV model. Appendix A
Funding Information:
This research was supported by the National Natural Science Foundation of China (Grant No. 51678044), the Fundamental Research Funds for the Central Universities (NO. 2017JBZ106), China, the Hong Kong Polytechnic University [1-BE2J], and the ERC Starting Grant #678799 for the SILCI project (Social Influence and disruptive Low Carbon Innovation). We would also thank Dr. Mike Bithell for discussing with us about the development and application of the SelfSim-EV model.
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/3/20
Y1 - 2020/3/20
N2 - Cost-related factors (e.g., subsides) play a vital role in the diffusion of Electric Vehicle (EV). However, it remains unclear how these factors would influence the diffusion and further the associated urban elements (e.g., infrastructures) at the micro scale. In response, this paper tried to quantify the influence of two types of cost-related factors on the adoption of Electric Vehicle (EV), namely upfront cost and usage-related cost, using purchase subsides and fuel prices as examples, respectively. An agent-based integrated micro-simulation model (SelfSim-EV) was used here to simulate how the EV market in Beijing might evolve from 2016 to 2020, within several “what-if” scenarios considering different Plug-in Hybrid Electric Vehicle (PHEV) subsides, petrol prices and electricity prices. The results suggested that 1) doubling the PHEV subsidy would make PHEV price competitive and thus increase the PHEV sale from around zero to 2500 in 2019. The PHEV sale price increases by around 3500 RMB (from around 261,000 to 264,500 RMB) due to the increase in the PHEV penetrate rate. This further gives rise to the changes in those urban elements connected with the EV market, including the urban environment, electricity and infrastructure systems, especially at the disaggregate level; 2) both electricity and petrol prices have little influence on the adoption of EVs at the macro level (i.e. the city level), but they do influence the spatial distributions of both CV and EV owners (based on the analyses of their residential locations) and further geographical distributions of vehicular emissions, EV-related facilities (e.g., charging posts) and electricity demand of EV at multiple resolutions, ranging from the facility level to district level.
AB - Cost-related factors (e.g., subsides) play a vital role in the diffusion of Electric Vehicle (EV). However, it remains unclear how these factors would influence the diffusion and further the associated urban elements (e.g., infrastructures) at the micro scale. In response, this paper tried to quantify the influence of two types of cost-related factors on the adoption of Electric Vehicle (EV), namely upfront cost and usage-related cost, using purchase subsides and fuel prices as examples, respectively. An agent-based integrated micro-simulation model (SelfSim-EV) was used here to simulate how the EV market in Beijing might evolve from 2016 to 2020, within several “what-if” scenarios considering different Plug-in Hybrid Electric Vehicle (PHEV) subsides, petrol prices and electricity prices. The results suggested that 1) doubling the PHEV subsidy would make PHEV price competitive and thus increase the PHEV sale from around zero to 2500 in 2019. The PHEV sale price increases by around 3500 RMB (from around 261,000 to 264,500 RMB) due to the increase in the PHEV penetrate rate. This further gives rise to the changes in those urban elements connected with the EV market, including the urban environment, electricity and infrastructure systems, especially at the disaggregate level; 2) both electricity and petrol prices have little influence on the adoption of EVs at the macro level (i.e. the city level), but they do influence the spatial distributions of both CV and EV owners (based on the analyses of their residential locations) and further geographical distributions of vehicular emissions, EV-related facilities (e.g., charging posts) and electricity demand of EV at multiple resolutions, ranging from the facility level to district level.
KW - Agent-based model
KW - Electric vehicle
KW - Electricity price
KW - Impact assessment
KW - Petrol price
KW - Subsidy
UR - http://www.scopus.com/inward/record.url?scp=85076217018&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2019.119479
DO - 10.1016/j.jclepro.2019.119479
M3 - Journal article
AN - SCOPUS:85076217018
SN - 0959-6526
VL - 250
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 119479
ER -