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Probabilistic Modeling and Statistical Analysis of Aggregated Electric Vehicle Charging Station Load

机译：电动汽车充电站总负荷的概率建模与统计分析

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摘要

The number of electric vehicles is increasing worldwide. The charging of a single electric vehicle can draw several kilowatts of power, and the aggregate effects of charging thousands of electric vehicles on electric power system infrastructure, operation, and planning must be considered. An important tool in studying the integration of electric vehicles and developing associated technologies and controls within the framework of the smart grid are probabilistic models of charging station load. This article identifies, evaluates, and proposes probabilistic models and analyzes the statistical characteristics of aggregated electric vehicle charging station load. A data-driven approach is taken, using measured time-stamped power consumption from charging stations to formulate and evaluate suitable parametric probabilistic models. The influence of time-of-use pricing on electric vehicle charging station load characteristics is also examined. Two data sets-one from Washington State, the other from San Diego, CA-each covering over 2 years, are used to create the models.
机译：全球电动汽车的数量正在增加。单个电动汽车的充电会消耗几千瓦的功率，因此必须考虑为数千辆电动汽车充电对电力系统基础设施，运行和计划的总体影响。充电站负荷的概率模型是研究电动汽车集成以及在智能电网框架内开发相关技术和控制的重要工具。本文确定，评估并提出了概率模型，并分析了电动汽车充电站总负荷的统计特性。采用数据驱动的方法，使用从充电站测得的带时间戳的功耗来制定和评估合适的参数概率模型。还研究了分时定价对电动汽车充电站负载特性的影响。使用两个数据集（一个来自华盛顿州，另一个来自加利福尼亚州圣地亚哥）来建立模型，每个数据集覆盖2年。

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