TY - JOUR
T1 - The role of the license plate lottery policy in the adoption of Electric Vehicles: A case study of Beijing
AU - Zhuge, Chengxiang
AU - Wei, Binru
AU - Shao, Chunfu
AU - Shan, Yuli
AU - Dong, Chunjiao
PY - 2020/4/1
Y1 - 2020/4/1
N2 - Policy is an influential factor to the purchase and usage of Electric Vehicles (EVs). This paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in Beijing, China. An agent-based spatial integrated urban model, SelfSim-EV, is employed to investigate how the policy may influence the uptake of EVs over time at the individual level. Two types of “what-if” scenario were set up to explore how the methods to allocate the vehicle purchase permits and the number of permits might influence the EV market expansion from 2016 to 2020. The results suggested that 1) both the allocation methods and the number of purchase permits could heavily influence the uptake of EVs and further its impacts on vehicular emissions, energy consumption and urban infrastructures; 2) compared to the baseline, both scenarios got significantly different spatial distributions of vehicle owners, transport facilities, vehicular emissions and charging demand at the multiple resolutions; 3) SelfSim-EV was found as a useful tool to quantify the nonlinear relationships between the increase of EV purchasers and the demand for transport facilities and electricity, and also to capture some unexpected results coming out from the interactions in the complex dynamic urban system.
AB - Policy is an influential factor to the purchase and usage of Electric Vehicles (EVs). This paper is focused on the license plate lottery policy, a typical vehicle purchase restriction in Beijing, China. An agent-based spatial integrated urban model, SelfSim-EV, is employed to investigate how the policy may influence the uptake of EVs over time at the individual level. Two types of “what-if” scenario were set up to explore how the methods to allocate the vehicle purchase permits and the number of permits might influence the EV market expansion from 2016 to 2020. The results suggested that 1) both the allocation methods and the number of purchase permits could heavily influence the uptake of EVs and further its impacts on vehicular emissions, energy consumption and urban infrastructures; 2) compared to the baseline, both scenarios got significantly different spatial distributions of vehicle owners, transport facilities, vehicular emissions and charging demand at the multiple resolutions; 3) SelfSim-EV was found as a useful tool to quantify the nonlinear relationships between the increase of EV purchasers and the demand for transport facilities and electricity, and also to capture some unexpected results coming out from the interactions in the complex dynamic urban system.
U2 - 10.1016/j.enpol.2020.111328
DO - 10.1016/j.enpol.2020.111328
M3 - Article
VL - 139
JO - Energy Policy
JF - Energy Policy
SN - 0301-4215
M1 - 111328
ER -