Scheduling EV charging with uncertain departure times

L. Narbondo, Andres Ferragut, Fernando Paganini

Research output: Contribution to journalArticleScientificpeer-review


In an EV charging facility, with multiple vehicles requesting charge simultaneously, scheduling becomes crucial to provide adequate service under vehicle sojourn time constraints. However, these departure times may not be known accurately, and typical policies such as Earliest-Deadline- First or Least-Laxity-First are affected by this uncertainty in information. In this paper, we analyze the performance of these policies under uncertain deadlines, using a meanfield approach. We characterize the deviation in individual attained service as a function of the uncertainty. Since incentives appear to under-report deadlines in order to be prioritized, we analyze a simple modification of the policies to enforce incentive compatibility. Simulation experiments are carried out with a practical data set.
Original languageEnglish
Pages (from-to)10-15
Number of pages6
JournalACM SIGMETRICS Performance Evaluation Review
Issue number3
Publication statusPublished - 2022
Externally publishedYes


  • EV Charging
  • Scheduling
  • Uncertainty


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