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GIS-driven analysis of e-mobility in urban areas: An evaluation of the impact on the electric energy grid

机译:GIS驱动的城市电动交通分析:对电网的影响评估

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摘要

This paper investigates the potential of electric vehicles to meet the mobility demand currently met by conventional fuel vehicles and explores the application of G1S datasets to geo-reference the electric energy demand resulting from their deployment on large geographical areas. The study is based on driving patterns collected from conventional fuel vehicles in the Italian provinces of Modena and Firenze by means of on-board GPS systems. The analysis is carried out over one month, considering approximately 28,000 vehicles and 36 million kilometres. Two types of battery electric vehicles and five recharging behavioural models are considered, to evaluate the trips and the fleet share suitable to be served by EVs, by following all the trips and parking sequences in the databases. This allows deriving the impact on the electricity grid of the electrification of urban vehicles in terms of additional electric energy demand and its geographical distribution. The results show that more than 80% of the urban trips can be covered by electric vehicles and that an urban fleet share between 8% and 28% could be replaced by the current generation of electric vehicles without any change in their driving patterns. The derived electric energy demand increase remains below 5% of the total electric energy demand, and below 20% of the domestic electric energy demand in the analysed areas. The geographical analysis shows in detail how this additional demand is distributed over the areas analysed, and how it compares with the already available recharging infrastructures in the two provinces. A complete description of the model developed is provided, focusing on the potential of CIS datasets to address the integration of electric vehicles in urbanised areas.
机译:本文研究了电动汽车满足传统燃料汽车目前满足的机动性需求的潜力,并探索了G1S数据集在地理上参考其在大地理区域中部署所产生的电能需求的应用。这项研究基于通过车载GPS系统从意大利摩德纳和佛罗伦萨的传统燃油汽车收集的驾驶模式。分析进行了一个多月,涉及大约28,000辆汽车和3600万公里。通过跟踪数据库中的所有行程和停车顺序,考虑了两种类型的电池电动汽车和五个充电行为模型,以评估适合电动汽车服务的行程和车队份额。这允许根据额外的电能需求及其地理分布,得出城市车辆电气化对电网的影响。结果表明,电动汽车可以覆盖超过80%的城市旅行,并且在不改变驾驶方式的情况下,当前的电动汽车可以代替8%至28%的城市车队。在分析区域内,得出的电能需求增长仍低于总电能需求的5%,而仍低于国内电能需求的20%。地理分析详细显示了这种额外需求如何在所分析的区域中分布,以及如何与两个省的现有充电基础设施进行比较。提供了所开发模型的完整说明,重点介绍了CIS数据集解决城市化地区电动汽车集成的潜力。

著录项

  • 来源
    《Applied Energy》 |2014年第1期|94-116|共23页
  • 作者单位

    European Commission - Directorate General Joint Research Centre, Institute for Energy and Transport, Sustainable Transport Unit, via Enrico Fermi 2749, Ispra 21027, Italy;

    European Commission - Directorate General Joint Research Centre, Institute for Energy and Transport, Sustainable Transport Unit, via Enrico Fermi 2749, Ispra 21027, Italy;

    European Commission - Directorate General Joint Research Centre, Institute for Energy and Transport, Sustainable Transport Unit, via Enrico Fermi 2749, Ispra 21027, Italy;

    European Commission - Directorate General Joint Research Centre, Institute for Energy and Transport, Sustainable Transport Unit, via Enrico Fermi 2749, Ispra 21027, Italy;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    CIS driving patterns; Activity data; Urban mobility; Electric vehicles; Geo-referenced electric energy demand;

    机译:CIS驾驶模式;活动数据;城市交通;电动汽车;地理参考电能需求;

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