Stochastic charging coordination method for electric vehicle (EV) aggregator considering uncertainty in EV departures

Youngwook Kim, Seongbae Kong, Sung Kwan Joo

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


This paper presents a stochastic method for an electric vehicle (EV) aggregator to coordinate EV charging schedule considering uncertainty in EV departures. The EV aggregator is responsible for managing the charging schedule of EVs while participating in the electricity markets. The managed EV charging can provide additional revenues to the aggregator from regulation market participation and charging cost reductions to EV owners. The aggregator needs to coordinate the charging schedule considering various uncertain factors such as electricity market prices and the stochastic characteristics of EVs. In this paper, the EV charging scheduling problem incorporating uncertainty in EV departures is formulated as a stochastic optimization problem. A stochastic optimization method is used to solve the EV charging scheduling problem. Latin hypercube sampling (LHS) and a scenario-reduction method are also applied to reduce the computational efforts of the proposed method. The results of a numerical example are presented to show the effectiveness of the proposed stochastic EV charging coordination method.

Original languageEnglish
Pages (from-to)1049-1056
Number of pages8
JournalJournal of Electrical Engineering and Technology
Issue number5
Publication statusPublished - 2016 Sept


  • EV aggregator
  • Electrical vehicle
  • Regulation
  • Stochastic EV departure

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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