期刊
IEEE ACCESS
卷 11, 期 -, 页码 11860-11870出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2023.3242115
关键词
Road transportation; Batteries; Road traffic; Europe; Charging stations; Urban areas; Electric vehicles; electric mobility; BEV; charging stations; highways; transportation
This paper assesses the impact of electric vehicle charging demand on the service areas of the Italian highway network. It proposes a methodology to forecast the future charging needs for each service area based on traffic data, considering both energy and power requirements during daily traffic peaks. The results show a significant impact, particularly in terms of power demand with peaks between two and three megawatts. The methodology developed is applicable for similar planning in other highway or suburban roadway contexts.
In recent years, market trends are confirming the increasing use of electric vehicles for private mobility. The use of such vehicles is inevitably affecting highway contexts as well. Therefore, highway network operators need to plan for the installation of adequate infrastructure to enable and manage the growing demand for fast charging expected in the coming years. This paper aims to assess the impact that this charging demand may have on the service areas (SAs) of the highway network operated by Autostrade per l'Italia. Starting from available traffic data, this paper proposes a methodology to forecast, for each service area, the future charging needs of EVs on a daily, monthly, and yearly basis. The analysis considers both the energy and the power that needs to be made available to ensure charging during daily traffic peaks. The results show that the impact generated by EVs will be generally significant, especially in terms of power demands with peaks between two and three megawatts. The methodology developed is entirely general and therefore applicable for similar planning in other highway or suburban roadway contexts. The validity of the developed methodology and the made assumptions have been preliminary confirmed through an initial set of data collected from one of the charging stations installed in one representative service area.
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