Stochastic Load Modeling of High-Power Electric Vehicle Charging - A Norwegian Case Study

Eirik Ivarsøy, B. N. Torsæter, M. Korpås
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引用次数: 4

Abstract

In recent years, the number of electric vehicles (EVs) has increased rapidly. Due to technological advancement, government policies and the focus on reducing greenhouse gas emission, the growth can be expected to continue. Home charging of EVs will often be sufficient for short-distance travel and daily routines. However, EVs still have a limited range. Thus, for long-distance travel, a network of fast charging stations (FCS) is needed. The stochastic nature, high power demand and short duration of EV fast charging, make it in many cases a grid capacity issue rather than an energy issue. Therefore, knowledge about the load profile of FCSs is important. In this paper, a model is developed for the simulation of the aggregated load profile of an FCS. The FCS load model includes a mobility model based on actual traffic flow, EV charging curves and temperature-dependent EV efficiency. Simulations are performed using the Monte Carlo simulation technique, to get a daily load profile for the FCS. Real-world data for the studied FCS in Norway is compared with the results from the simulation to analyze the performance of the FCS load model. The developed load profile for the FCS has a high peak-to-average power ratio, which indicates that the socioeconomic profitability of fast charging stations still is low.
大功率电动汽车充电随机负荷建模——以挪威为例
近年来,电动汽车(ev)的数量迅速增加。由于技术进步、政府政策和对减少温室气体排放的关注,预计增长将继续。电动汽车的家庭充电通常足以满足短途旅行和日常生活。然而,电动汽车的续航里程仍然有限。因此,对于长途旅行来说,需要一个快速充电站网络(FCS)。电动汽车快速充电的随机性、高功率需求和短持续时间,使其在许多情况下成为电网容量问题,而不是能量问题。因此,了解fcs的负载分布是很重要的。在本文中,建立了一个模型来模拟FCS的总负荷分布。FCS负荷模型包括基于实际交通流量、电动汽车充电曲线和温度依赖的电动汽车效率的移动性模型。使用蒙特卡罗模拟技术进行模拟,以获得FCS的每日负载概况。将挪威FCS的实际数据与仿真结果进行比较,分析FCS负荷模型的性能。快速充电站的负荷曲线具有较高的峰值-平均功率比,这表明快速充电站的社会经济效益仍然较低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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