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Identifying new EV charging station locations based on user trip data

Breemen, J. van and Sigtermans, A.J.H. and Kliffen, K.Y. (2015) Identifying new EV charging station locations based on user trip data. Bachelor's Thesis, Computing Science.

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Abstract

This study focuses on the growth of electric vehicle supporting infrastructure. Over the past years, electric vehicle usage has been on the rise, and technologies that have been researched for years start to get ready for the consumer market. The use of electric vehicles is growing rapidly, and the Netherlands currently has one of the highest coverages in both charging stations as well as electric vehicles (of course, in relation to the number of inhabitants). For example, the Netherlands currently has over 7600 charging stations. That's the highest number in any of the EU countries, with Germany (a substantially bigger country in terms of both population and area) taking a second place with approximately 3800 charging stations. Though electric vehicles are being adopted quickly, the main bottleneck for massive growth remains the limited range. Whilst researchers, engineers and car manufacturers focus on increasing battery capacity (with very promising results shown by companies such as Tesla), it is up to local governments, infrastructure providers and electric utility companies to improve the infrastructure for recharging electric vehicles. This study will focus on helping these last mentioned parties to gather insights on where to place new charging stations, based on the needs of both current electric vehicle drivers, as well as future electric vehicle drivers. By gathering data on driving behaviour (trips), processing it (adding weights and distinguishing variables), and analyse it, new charging station locations will be identified, helping the before mentioned parties to grow the electric vehicle infrastructure in an efficient manner, onwards to a 'global' coverage, similar to that of fossil fuels. Though this study focuses on the situation in the Netherlands, which already has a high density of charging stations, it will be of great importance to other countries that are in an earlier stage of electric vehicle infrastructure development. The Netherlands is a good reference case since a 'general' coverage has already been realised, and efficient and optimised decisions hence are of greater importance. Furthermore, the methods described for identifying charging stations will not only be applicable to supplying electricity (recharging facilities) but can, with the right interpretation and constraints, also be applied on other (renewable) fuels that are not yet broadly available.

Item Type: Thesis (Bachelor's Thesis)
Degree programme: Computing Science
Thesis type: Bachelor's Thesis
Language: English
Date Deposited: 15 Feb 2018 08:06
Last Modified: 15 Feb 2018 08:06
URI: http://fse.studenttheses.ub.rug.nl/id/eprint/13032

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