Resource Aware Pricing for Electric Vehicle Charging
Resource Aware Pricing for Electric Vehicle Charging
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DOI：
10.1016/j.automatica.2022.110733
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
Cesar Santoyo;Gustav Nilsson;S. Coogan
中科院分区：
文献类型：
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作者：
Cesar Santoyo;Gustav Nilsson;S. Coogan
电动车辆充电设施向用户提供其容量受限的充电和停车，但需要付费。随着电动汽车的普及，过度利用资源的可能性也在增加。在本文中，我们研究了充电设施设置的价格如何影响指定的资源利用水平被超过的可能性。具体来说，我们提出了概率边界上的充电点的数量和所需的总电源在一个设施的基础上到达车辆的特性。我们假设充电设施向每个用户提供一组不同且固定的充电率，或者允许用户决定充电期限，由此确定充电率。用户随机到达，需要随机的费用。此外，每个用户都有一个随机的不耐烦因素，量化他们的时间价值，以及一个随机的期望时间停留在一个特定的位置。假设合理的用户行为，并与随机参数的概率分布的知识，我们提出了高置信区间的车辆停在车站的总数和总的功率使用的所有车辆积极充电。我们演示了如何使用这些边界的充电设施，以确定适当的定价参数和调查通过蒙特-卡罗模拟案例研究的紧密性的界限。
Electric vehicle charging facilities offer their capacity constrained electric charge and parking to users for a fee. As electric vehicle adoption grows, so too does the potential for excessive resource utilization. In this paper, we study how prices set by the charging facility impact the likelihood that specified resource utilization levels are exceeded. Specifically, we present probabilistic bounds on the number of charging spots and the total power supply needed at a facility based on the characteristics of the arriving vehicles. We assume the charging facility either offers a set of distinct and fixed charging rates to each user or allows the user to decide a charging deadline, from which a charging rate is determined. Users arrive randomly, requiring a random amount of charge. Additionally, each user has a random impatience factor that quantifies their value of time, and a random desired time to stay at a particular location. Assuming rational user behavior, and with knowledge of the probability distribution of the random parameters, we present high-confidence bounds on the total number of vehicles parked at the station and the aggregate power use of all vehicles actively charging. We demonstrate how these bounds can be used by a charging facility to determine appropriate pricing parameters and investigate through a Monte–Carlo simulation case study the tightness of the bounds.