On-Line Event-Driven Scheduling for Electric Vehicle Charging via Park-and-Charge

Fanxin Kong, Qiao Xiang, Linghe Kong, Xue Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Large-scale charging stations become indispensable infrastructure to support the rapid proliferation of electric vehicles. Their operation modes have drawn great attention from both academia and industry. One promising mode called park-and-charge has been recently introduced. This new mode allows customers to park their electric vehicles at a parking lot, where the vehicles are charged during the parking time. Several small-scale experiments, such as the V-Charge project and General Motors' E-Motor plant, have demonstrated its potential. A key enabler for deploying this mode to large-scale stations is effective and efficient charging load scheduling methods. Most existing works confine to the time-driven scheduling policy due to their sole focus on the charging service. Applying their solutions to the park-and-charge mode would jeopardize the unitization of charging resource or cause frequent charging mode switching. This inapplicability motivates us to explore the feasibility and benefits of exploiting the event-driven scheduling policy in park-and-charge systems. Further, to better characterize charging load in this mode, we propose to adopt a metered model, by which a system gains value in proportion to the served charging demand. To be specific, the objective of this paper is to carry out both theoretical and experimental analysis for event-driven algorithms adapted to this metered model. We leverage both the competitive analysis and resource augmentation to demonstrate the non-constant and constant performance bounds for the earliest-deadline-first and highest-value-first algorithms respectively. Moreover, we provide a stronger theoretical result, i.e., the performance bound for the whole class of work-conserving scheduling algorithms. Through extensive simulations, we validate the proposed theoretical results and further provide interesting findings from the in-depth analysis of the simulation results.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE Real-Time Systems Symposium, RTSS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages69-78
Number of pages10
ISBN (Electronic)9781509053025
DOIs
StatePublished - Jul 2 2016
Externally publishedYes
Event2016 IEEE Real-Time Systems Symposium, RTSS 2016 - Porto, Portugal
Duration: Nov 29 2016Dec 2 2016

Publication series

NameProceedings - Real-Time Systems Symposium
Volume0
ISSN (Print)1052-8725

Other

Other2016 IEEE Real-Time Systems Symposium, RTSS 2016
CountryPortugal
CityPorto
Period11/29/1612/2/16

Keywords

  • Electric Vehicles
  • Event-Driven
  • On-Line scheduling
  • Park-and-Charge

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'On-Line Event-Driven Scheduling for Electric Vehicle Charging via Park-and-Charge'. Together they form a unique fingerprint.

  • Cite this

    Kong, F., Xiang, Q., Kong, L., & Liu, X. (2016). On-Line Event-Driven Scheduling for Electric Vehicle Charging via Park-and-Charge. In Proceedings - 2016 IEEE Real-Time Systems Symposium, RTSS 2016 (pp. 69-78). [7809844] (Proceedings - Real-Time Systems Symposium; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTSS.2016.016