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ToolsLiu, Shuohan, Xia, Xu, Cao, Yue, Ni, Qiang, Zhang, Xu and Xu, Lexi (2021) Reservation-based EV charging recommendation concerning charging urgency policy. Sustainable Cities and Society, 74. ISSN 2210-6707
Full text not available from this repository. (Request a copy)Abstract
Electric Vehicles (EVs) are environmental friendly comparing with traditional internal combustion vehicles (ICVs), and have great application potential to achieve green transportation. However, due to the battery technology under development, the charging time of EVs is still longer than refuelling time of ICVs. Importantly, CS-Selection scheme (which/where to charge) and charging scheduling (when/whether to charge) are key solutions, for coping with long charging time and uneven distribution of Charging Stations (CSs) in urban city. In this paper, we propose an Urgency First Charging (UFC) scheduling policy, which orders EVs via their charging urgency (calculated by their charging demand and remaining parking duration). With the underlying UFC policy, we further propose a reservation-based CS-Selection scheme that selects the optimal CS with the minimum trip duration (summation of travelling time through CS, and the charging time spent at CS), where the EVs would further report their reservations to help anticipate the service congestion status of CSs in future. We have conducted simulations through Helsinki's city traffic scenarios. The simulation results show that our proposed CS-Selection scheme has advantages in improving users quality of experience, which shortens the overall trip duration of EVs and fully charges more EVs before departure deadline.
| Item Type: | Article |
|---|---|
| Additional Information: | Funding Information: This work is supported by Science and Technology Project of State Grid Corporation of China (SGFJXT00TXJS2000313), National Key R&D Program of China (No. 2020YFB1806700) and Natural Science Basic Research Program of Shaanxi (Program No. 2019JQ-258). |
| Uncontrolled Keywords: | charging scheduling,charging urgency,cs-selection,electric vehicle,ev charging recommendation,geography, planning and development,civil and structural engineering,renewable energy, sustainability and the environment,transportation,sdg 7 - affordable and clean energy,sdg 11 - sustainable cities and communities ,/dk/atira/pure/subjectarea/asjc/3300/3305 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI Faculty of Science > Research Groups > Smart Emerging Technologies |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 01 Feb 2024 03:08 |
| Last Modified: | 29 Jan 2025 13:19 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/94333 |
| DOI: |
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