Mapping the charging demand for electric vehicles in 2050 from mobility habits

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
Noémie Jeannin, Alejandro Pena-Bello, Christophe Ballif, Nicolas Wyrsch
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引用次数: 0

Abstract

This paper proposes a method to spatially model and compare charging needs on the European scale, considering local disparities in population density, distance to city centres, car ownership and mobility habits. Mobility habits are modelled across Europe in terms of distance and time frame to elaborate scenarios of charging behaviour. The first step of the method is to calculate the density of electric vehicles with a resolution of 1 km2, according to the progressive electrification of the fleet each year between 2020 and 2050. The second step is to quantify the mobility of commuters using their driving distance to work areas and mobility statistics. The model is then applied in a case study in Switzerland to plan the public charging infrastructure required to satisfy the charging needs of the local population. Despite lower motorization rates and driving distances, the results show a stronger need for charging in cities. With 50% of commuters charging at work and 20% at home during the workday, the demand in the evening can be reduced by 50% in the suburban areas compared to the baseline scenario in which all commuters are charging at home in the evening. This model can be used to quantify the energy needs of commuters, plan the deployment of the charging infrastructure, or simulate the effect of policies.

Abstract Image

从出行习惯看 2050 年的电动汽车充电需求
本文提出了一种在欧洲范围内对充电需求进行空间建模和比较的方法,其中考虑到了各地在人口密度、与市中心的距离、汽车拥有量和移动习惯等方面的差异。从距离和时间框架的角度对整个欧洲的移动习惯进行建模,以制定充电行为方案。该方法的第一步是根据 2020 年至 2050 年期间每年逐步电气化的车队,以 1 平方公里的分辨率计算电动汽车的密度。第二步是利用通勤者到工作区域的驾驶距离和流动性统计数据,量化通勤者的流动性。然后将该模型应用于瑞士的一项案例研究,规划满足当地居民充电需求所需的公共充电基础设施。尽管机动化率和驾驶距离较低,但结果显示城市对充电的需求更为强烈。在工作日,50% 的通勤者在工作时充电,20% 的通勤者在家中充电,与所有通勤者晚上都在家中充电的基准情景相比,郊区晚上的需求可减少 50%。该模型可用于量化通勤者的能源需求、规划充电基础设施的部署或模拟政策效果。
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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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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