Capacity planning frameworks for electric vehicle charging stations with multiclass customers

Islam Safak Bayram, Ali Tajer, Mohamed Abdallah, Khalid Qaraqe

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)


In order to foster electric vehicle (EV) adoption, there is a strong need for designing and developing charging stations that can accommodate different customer classes distinguished by their charging preferences, needs, and technologies. By growing such charging station networks, the power grid becomes more congested and, therefore, controlling charging requests should be carefully aligned with the available resources. This paper focuses on an EV charging network equipped with different charging technologies and proposes two frameworks. In the first framework, appropriate for large networks, the EV population is expected to constitute a sizable portion of the light duty fleets. This necessitates controlling the EV charging operations to prevent potential grid failures and distribute the resources efficiently. This framework leverages pricing dynamics in order to control the EV customer request rates and to provide a charging service with the best level of quality of service (QoS). The second framework, on the other hand, is more appropriate for smaller networks, in which the objective is to compute the minimum amount of resources required to provide certain levels of QoS to each class. The results show that the proposed frameworks ensure grid reliability and lead to significant savings in capacity planning.

Original languageEnglish
Article number7060713
Pages (from-to)1934-1943
Number of pages10
JournalIEEE Transactions on Smart Grid
Issue number4
Early online date13 Mar 2015
Publication statusPublished - 31 Jul 2015


  • capacity planning
  • distributed control
  • electric vehicles (EVs)
  • performance evaluation
  • pricing


Dive into the research topics of 'Capacity planning frameworks for electric vehicle charging stations with multiclass customers'. Together they form a unique fingerprint.

Cite this