We analyze daily charging demand patterns of electric vehicles at DC fast charging stations along the German autobahn for an average week in 2020. For this we develop an agent based simulation tool based on current empirical mobility data. Our results show that already in 2020 about 1,000 charging processes per charging location and day might be realistic. In order to avoid long waiting times these charging locations should be equipped with about 20 charging points. A utilization rate of up to 80% makes a profitable operation of these stations highly probable. A sensitivity analysis indicates main parameters which influence the throughput of electric vehicles significantly.
A successful transformation of the energy and transportation sector is one of the main targets for our society today. Battery electric vehicles can play a key role in future renewable-based energy supply systems because of their ability to store electrical power. Additionally, they provide significant charging flexibility due to the long parking durations. In this paper, we provide insights into the temporal and power-specific flexibility behavior of three different vehicle fleets. These fleets are pool vehicles of office employees, a public authority, and a logistics company. Several parameters, such as the average charging power per charging event or the average plug-in duration per charging event, are discussed. Additionally, we investigate different charging rates and their impact on the temporal flexibility of the charging events. The data analysis shows that the logistics site has the most homogeneous charging profile as well as high charging flexibility, in contrast to the office and public agency site. The results are of significant importance for future applications in the field of smart charging and ancillary services provision.
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