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

机译:大功率电动汽车充电的随机负荷建模-挪威案例研究

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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.
机译:近年来,电动汽车(EV)的数量迅速增加。由于技术的进步,政府政策以及对减少温室气体排放的关注,预计这种增长将持续下去。电动汽车的家用充电通常足以满足短途旅行和日常工作的需要。但是,电动汽车的范围仍然有限。因此,对于长途旅行,需要快速充电站(FCS)的网络。随机性,高功率需求以及电动汽车快速充电的持续时间短,使得它在许多情况下成为电网容量问题,而不是能源问题。因此,有关FCS负载曲线的知识很重要。在本文中,开发了一个模型,用于模拟FCS的总负荷曲线。 FCS负载模型包括基于实际交通流量,电动汽车充电曲线和与温度相关的电动汽车效率的移动性模型。使用蒙特卡洛模拟技术进行模拟,以获得FCS的每日负荷曲线。将挪威研究的FCS的实际数据与仿真结果进行比较,以分析FCS负载模型的性能。为FCS开发的负载曲线具有较高的峰均功率比,这表明快速充电站的社会经济效益仍然很低。

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