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World Electric Vehicle Journal is published by MDPI from Volume 9 issue 1 (2018). Articles in this Issue were published by The World Electric Vehicle Association (WEVA) and its member the European Association for e-Mobility (AVERE), the Electric Drive Transportation Association (EDTA), and the Electric Vehicle Association of Asia Pacific (EVAAP). They are hosted by MDPI on mdpi.com as a courtesy and upon agreement with AVERE.
Open AccessArticle

A Model for Public Fast Charging Infrastructure Needs

1
Fraunhofer Institute for Systems and Innovation research ISI, Breslauer Strasse 48, 76139 Karlsruhe, Germany
2
Chalmers University of Technology, Energy and Environment, 412 96 Gothenburg, Sweden
3
Exigal Technologies AB, Blidvädersgatan 17E, 418 30 Gothenburg, Sweden
*
Author to whom correspondence should be addressed.
World Electr. Veh. J. 2016, 8(4), 943-954; https://doi.org/10.3390/wevj8040943
Published: 30 December 2016
PDF [619 KB, uploaded 17 May 2018]

Abstract

Plug-in electric vehicles can reduce GHG emissions although the low availability of public charging infra-structure combined with short driving ranges prevents potential users from adoption. The rollout and opera-tion, especially of public fast charging infrastructure, is very costly. Therefore, policy makers, car manufac-turers and charging infrastructure providers are interested in determining a number of charging stations that is sufficient. Since most studies focus on the placement and not on the determination of the number of charging stations, this paper proposes a model for the quantification of public fast charging points.
We first analyze a large database of German driving profiles to obtain the viable share of plug-in electric vehicles in 2030 and determine the corresponding demand for fast charging events. Special focus lies on a general formalism of a queuing system for charging points. This approach allows us to quantify the capac-ity provided per charging point and the required quantity. Furthermore, we take a closer look on the sto-chastic occupancy rate of charging points for a certain service level and the distribution of the time users have to wait in the queue. When applying this model to Germany, we find about 15,000 fast charging points with 50 kW necessary in 2030 or ten fast charging point per 1,000 BEVs. When compared with existing charging data from Sweden, this is lower than the currently existing 36 fast charging points per 1,000 BEVs. Furthermore, we compare the models output of charging event distribution over the day with that of the real data and find a qualitatively similar load of the charging network, though with a small shift towards later in the day for the model.
Keywords: Charging infrastructure; queuing model; stochastic occupancy rate of charging points; electric vehicle Charging infrastructure; queuing model; stochastic occupancy rate of charging points; electric vehicle
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Gnann, T.; Goldbach, D.; Jakobsson, N.; Plötz, P.; Bennehag, A.; Sprei, F. A Model for Public Fast Charging Infrastructure Needs. World Electr. Veh. J. 2016, 8, 943-954.

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World Electr. Veh. J. EISSN 2032-6653 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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