4.7 Article

Sizing of electric vehicle charging stations with smart charging capabilities and quality of service requirements

期刊

SUSTAINABLE CITIES AND SOCIETY
卷 70, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scs.2021.102872

关键词

Electric vehicles; Charging stations; Sizing; Smart charging; Flexibility

资金

  1. European Union [863876]
  2. European Union under the Marie SkodowskaCurie Grant [754462]
  3. Marie Curie Actions (MSCA) [754462] Funding Source: Marie Curie Actions (MSCA)

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The increasing adoption of electric vehicles is linking the transportation and electricity systems through charging stations. Smart Charging technologies have the potential to reduce operational costs and optimize the use of charging facilities, improving service quality for clients.
The increasing penetration of electric vehicles (EVs) inherently couples the transportation system with the electricity system through charging stations (CSs). Today's regulatory context highly incentivizes CS infra-structure investments that are expected to have a significant impact on reducing air pollution, cutting emissions and promoting environmentally sustainable cities. The Sizing problem of a CS typically concerns the minimi-zation of the investment cost for charging facilities, subject to the CS being able to fulfill a certain level of charging requests. Several studies have shown the potential of Smart Charging technologies, towards controlling the charging profiles of EVs, so as to achieve a lower operational cost or a lower peak to average power con-sumption ratio for the CS, by shifting the charging of some EVs. By making more efficient use of charging fa-cilities, Smart Charging can also help reducing the amount of chargers required in order to achieve a certain Quality of Service (QoS) for the CS's clients. In this paper we solve the CS's sizing problem (i.e. decisions on number and types of installed chargers) through an optimization framework that minimizes the investment cost of CS operators, subject to achieving a certain QoS for their clients (EV owners). In particular, we extend the existing CS sizing models by taking into account also the smart charging capabilities during operation. We present a novel formulation for the QoS level of the CS using chance-constraints and propose some relaxations that constitute the problem solvable. Finally, we present a methodology that enhances the scalability of the optimal sizing algorithm. The proposed methodology is able to offer valuable services to CS operators in competitive environments.

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