Optimizing the allocation of fast charging infrastructure along the German autobahn

Patrick Jochem, Carsten Brendel (), Melanie Reuter-Oppermann (), Wolf Fichtner () and Stefan Nickel ()
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Carsten Brendel: Karlsruhe Institute of Technology (KIT)
Melanie Reuter-Oppermann: Karlsruhe Institute of Technology (KIT)
Wolf Fichtner: Karlsruhe Institute of Technology (KIT)
Stefan Nickel: Karlsruhe Institute of Technology (KIT)

Journal of Business Economics, 2016, vol. 86, issue 5, No 3, 513-535

Abstract: Abstract The allocation of fast charging stations is a severe investment for the future mobility system with electric vehicles. The allocation of the first charging stations influences the profitability of all other fast charging stations and should therefore be perfectly arranged. Hence, we applied and extended the flow-refueling location model (FRLM) developed by Capar et al. (Eur J Oper Res 227(1):142–151, 2013) to the German autobahn with a focus on the states Baden-Württemberg and Bavaria with 595 nodes and 3569 highway km. Our model extension comprehends mainly the inclusion of the access distance for traffic participants to their closest network node. In order to analyze the impact of different vehicle ranges and the desired coverage of flows we defined four scenarios. The results indicate the significance of vehicle range and the desired coverage value. 20 optimally allocated fast charging stations along the highways lead already to a coverage of about 62 % (100 km vehicle range) or even 83 % (150 km vehicle range) of all trips. A complete coverage of trips requires at least 50 (150 km vehicle range), 77 (100 km vehicle range) or even 84 (70 km vehicle range) fast charging stations. The last 30 % coverage leads to a tripling of charging stations. Furthermore, a first estimation of the corresponding surcharge for fixed costs per charging process amounts to about 20 % of the total costs for a charging process.

Keywords: Fast charging station; Electric vehicle; Optimization; Allocation; Germany (search for similar items in EconPapers)
JEL-codes: C61 M20 O33 P48 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (12)

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DOI: 10.1007/s11573-015-0781-5

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