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  • A Preempted EV Charging Reservation System

    Submitted manuscript, 316 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

  • A Preempted EV Charging Reservation System

    Accepted author manuscript, 316 KB, PDF document

    Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License

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Electric Vehicle Charging Reservation Under Preemptive Service

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Yue Cao
  • Shuohan Liu
  • Ziming He
  • Xuewu Dai
  • Xiaoyan Xie
  • Ran Wang
  • Shengping Yu
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Publication date30/09/2019
Host publication IEEE International Conference on Industrial Artificial Intelligence (IAI) Proceedings 2019
PublisherIEEE
Number of pages6
ISBN (electronic)9781728135939
ISBN (print)9781728135946
<mark>Original language</mark>English
EventIEEE International Conference on Industrial Artificial Intelligence (IAI) -
Duration: 23/07/201925/07/2019

Conference

ConferenceIEEE International Conference on Industrial Artificial Intelligence (IAI)
Period23/07/1925/07/19

Conference

ConferenceIEEE International Conference on Industrial Artificial Intelligence (IAI)
Period23/07/1925/07/19

Abstract

Electric Vehicles (EV) are environment-friendly with lower CO2 emissions, and financial affordability (in term of battery based refuel) benefits. Here, when and where to recharge are sensitive factors significantly impacting the environmental and financial gains, these are still challenges to be tackled. In this paper, we propose a sustainable and smart EV charging scheme enables the preemptive charging functions for heterogeneous EVs equipped with various charging capabilities and brands. Our scheme intents to address the problems when EVs are with various ownerships and priority, in related to the services agreed with charging infrastructure operators. Particularly, the anticipated EVs' charging reservations information with heterogeneity (are multiscale) including their EV type, expected arrival time and charging waiting time at the charging stations (CSs), have been considered for design, planning and optimal decision making on the selection (i.e., where to charge) among the candidature CSs. We have conducted extensive simulation studies, by taking the realistic Helsinki city geographical and traffic scenarios as an example. The numerical results have confirmed that our proposed preemptive approach is better than the First-Come-First-Serve (FCFS) based system, associated with its significant improvement on the reservation feature in EV charging.