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.

电动汽车充电设施向用户收费提供容量受限的充电和停车。随着电动汽车的普及，资源过度利用的可能性也在增加。在本文中，我们研究了充电设施设定的价格如何影响超过指定资源利用率水平的可能性。具体来说，我们根据到达车辆的特征给出了充电点数量和设施所需总电源的概率界限。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截止日期，从中确定充电率。用户随机到达，需要随机收费。此外，每个用户都有一个随机的不耐烦因子来量化他们的时间价值，以及一个随机的希望在特定位置停留的时间。假设用户行为理性，并了解随机参数的概率分布，我们对停在车站的车辆总数和所有主动充电车辆的总用电量提出高置信界限。我们演示了充电设施如何使用这些界限来确定适当的定价参数，并通过蒙特卡洛模拟案例研究调查界限的紧密性。我们对停在车站的车辆总数和所有主动充电车辆的总用电量提出了高置信区间。我们演示了充电设施如何使用这些界限来确定适当的定价参数，并通过蒙特卡洛模拟案例研究调查界限的紧密性。我们对停在车站的车辆总数和所有主动充电车辆的总用电量提出了高置信区间。我们演示了充电设施如何使用这些界限来确定适当的定价参数，并通过蒙特卡洛模拟案例研究调查界限的紧密性。