A charging scheduling system for electric vehicles using vehicle-To-grid

Nicklas K. Breum, Martin N. Joergensen, Christian A. Knudsen, Laerke B. Kristensen, Bin Yang

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

3 Citations (Scopus)

Abstract

With the rise of sustainable energy sources, such as wind power, the energy production, and thus the energy price, fluctuates. Meanwhile, we are witnessing an increasing amount of electric vehicles, which soon will represent a substantial fraction of the electricity demand. Under this setting, the so-called vehicle-To-grid technology, which enables electric vehicles to sell electricity back to the power grid, appears to be an effective mean to reduce the charging costs for electric vehicles. We demonstrate a system that makes optimal scheduling for electric vehicle fleet owners using vehicle-To-grid. The principle of the scheduling is to charge electric vehicles when electricity is cheap and sell electricity back to the power grid when it is expensive, while making sure that the electric vehicles are sufficiently charged when they need to be used, e.g., 8 am in the morning. The system is integrated as part of aSTEP, a spatio-Temporal data analytics platform developed at Aalborg University. In collaboration with a transportation-As-A-service company in Denmark, the system is tested through a use case that involves an electric vehicle fleet.

Original languageEnglish
Title of host publicationProceedings - 2019 20th International Conference on Mobile Data Management, MDM 2019
Number of pages2
PublisherIEEE
Publication dateJun 2019
Pages351-352
Article number8788738
ISBN (Print)978-1-7281-3364-5
ISBN (Electronic)9781728133638
DOIs
Publication statusPublished - Jun 2019
Event20th International Conference on Mobile Data Management, MDM 2019 - Hong Kong, Hong Kong
Duration: 10 Jun 201913 Jun 2019

Conference

Conference20th International Conference on Mobile Data Management, MDM 2019
Country/TerritoryHong Kong
CityHong Kong
Period10/06/201913/06/2019
SponsorCroucher Foundation, Hong Kong Baptist University, Department of Computer Science, IEEE, IEEE Computer Society, IEEE Technical Committee on Data Engineering
SeriesProceedings - IEEE International Conference on Mobile Data Management
Volume2019-June
ISSN1551-6245

Keywords

  • Electric vehicles
  • Spatio temporal data analytics
  • Vehicle to grid

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