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Response of electric vehicle drivers to dynamic pricing of parking and charging services: risky choice in early reservations

机译:电动汽车驾驶员对停车和充电服务动态定价的反应:早期预订中的风险选择

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摘要

When clusters of electric vehicles charge simultaneously in urban areas, the capacity of the power network might not be adequate to accommodate the additional electricity demand. Recent studies suggest that real-time control strategies, like dynamic pricing of electricity, can spread the demand and help operators to avoid costly infrastructure investments. To assess the effectiveness of dynamic pricing, it is necessary to understand how electric vehicle drivers respond to uncertain future prices when they charge their vehicle away from home. Even when data is available from electric vehicle trials, the lack of variability in electricity prices renders them insufficient for this analysis. We resolve this problem by designing a survey where we observe the stated preferences of the respondents for hypothetical charging services. A novel feature of this survey is its interface, which resembles an online or smartphone application for parking-and-charging reservations. The time-of-booking choices are evaluated within a risky-choice modelling framework, where expected utility and non-expected utility specifications are compared to understand how people perceive price probabilities. In the progress, we bring together theoretical frameworks of forward-looking behaviour in contexts where individuals were subject to equivalent price uncertainties. The results suggest that a) the majority of the electric vehicle drivers are risk averse by choosing a certain price to an uncertain one and b) there is a non-linearity in their choices, with a disproportional influence by the upper end of the price distribution. This approach gives new perspectives in the way people plan their travel activities in advance and highlights the impact of uncertainty when managing limited resources in dense urban centres. Similar surveys and analyses could provide valuable insights in a wide range of innovative mobility applications, including car-sharing, ride-sharing and on-demand services.
机译:当在城市地区同时为电动汽车集群充电时,电网的容量可能不足以满足额外的电力需求。最近的研究表明,实时控制策略(例如动态电价)可以分散需求并帮助运营商避免昂贵的基础设施投资。为了评估动态定价的有效性,有必要了解电动汽车驾驶员在外出充电时如何应对不确定的未来价格。即使可以从电动汽车试验获得数据,但由于电价缺乏可变性,因此不足以进行此分析。我们通过设计调查来解决此问题,在调查中我们观察了受访者对假设收费服务的陈述偏好。该调查的一个新颖功能是其界面,它类似于用于停车和收费预订的在线或智能手机应用程序。在风险选择建模框架中评估预订时间选择,在该框架中比较预期效用和非预期效用规格,以了解人们如何看待价格概率。在此过程中,我们将在个体面临同等价格不确定性的情况下,汇集前瞻性行为的理论框架。结果表明,a)大多数电动汽车驾驶员通过将某个价格选择为不确定的价格来规避风险,并且b)他们的选择存在非线性,价格分布的上限会产生不成比例的影响。这种方法为人们提前计划旅行活动提供了新视角,并强调了在人口密集的城市中心管理有限资源时不确定性的影响。类似的调查和分析可以在广泛的创新出行应用中提供有价值的见解,包括汽车共享,乘车共享和按需服务。

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