An Interoperable Reservation System for Public Electric Vehicle Charging Stations: A Case Study in Germany

As the number of electric vehicles on the roads increases, new technologies and concepts such as fast/super-fast charging and dynamic pricing are developed and implemented respectively. With those innovations on the rise, reservation of charging stations for electric vehicles will play a pivotal role in seamlessly integrating them into the transportation and mobility system. In this paper we derive basic requirements for building interoperable reservation systems and identify four generic approaches to reservation. For designing the system model and engineering the charging station reservation system, we utilize the E-Mobility Systems Architecture framework. For one of the reservation types, we implement a proof-of-concept and demonstrate its usefulness by conducting a showcase in Bavaria, Germany. Further, we set up and conduct a simulation-based evaluation to compare the four different reservation types regarding their benefit to users and providers as well as overall system efficiency. To the best of our knowledge, this is the first contribution proposing an interoperable reservation system for electric vehicle charging. The results presented in this paper provide insights regarding the feasibility of the different reservation types under varying conditions.

[1]  Hua Qin,et al.  Charging scheduling with minimal waiting in a network of electric vehicles and charging stations , 2011, VANET '11.

[2]  Ralf Philipsen,et al.  Fast-charging station here, please! User criteria for electric vehicle fast-charging locations , 2016 .

[3]  Yue Cao,et al.  An Electric Vehicle Charging Management Scheme Based on Publish/Subscribe Communication Framework , 2016, IEEE Systems Journal.

[4]  Hermann de Meer,et al.  E-Mobility Systems Architecture: a model-based framework for managing complexity and interoperability , 2019 .

[5]  E. F. El-Saadany,et al.  Uncoordinated charging impacts of electric vehicles on electric distribution grids: Normal and fast charging comparison , 2012, 2012 IEEE Power and Energy Society General Meeting.

[6]  Yue Cao,et al.  Reservation Based Electric Vehicle Charging Using Battery Switch , 2018, 2018 IEEE International Conference on Communications (ICC).

[7]  Guy Doumeingts,et al.  Architectures for enterprise integration and interoperability: Past, present and future , 2008, Comput. Ind..

[8]  Samir Chatterjee,et al.  A Design Science Research Methodology for Information Systems Research , 2008 .

[9]  Liu Haoming,et al.  Reserving Charging Decision-Making Model and Route Plan for Electric Vehicles Considering Information of Traffic and Charging Station , 2018 .

[10]  Sonja Klingert,et al.  Seamless Electromobility , 2017, e-Energy.

[11]  Hye-Jin Kim,et al.  An Efficient Scheduling Scheme on Charging Stations for Smart Transportation , 2010, SUComS.

[12]  B. Sovacool,et al.  The demographics of decarbonizing transport: The influence of gender, education, occupation, age, and household size on electric mobility preferences in the Nordic region , 2018, Global Environmental Change.

[13]  Adrian Stoica,et al.  Security-Enriched Urban Computing and Smart Grid - First International Conference, SUComS 2010, Daejeon, Korea, September 15-17, 2010. Proceedings , 2010, International Conference on Security-Enriched Urban Computing and Smart Grid.

[14]  Hye-Jin Kim,et al.  Reservation-Based Charging Service for Electric Vehicles , 2011, ICA3PP.

[15]  Omprakash Kaiwartya,et al.  Toward Anycasting-Driven Reservation System for Electric Vehicle Battery Switch Service , 2019, IEEE Systems Journal.

[16]  Zita Vale,et al.  Dynamic electricity pricing for electric vehicles using stochastic programming , 2017 .

[17]  Jakub Zawieska,et al.  Smart city as a tool for sustainable mobility and transport decarbonisation , 2018 .