Capacity optimisation framework for fast charging stations operating under cold weather

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In this paper, we present a probabilistic capacity planning framework for electric vehicle (EV) fast charging stations that operate under cold weather. Existing literature on charging station modelling assumes that fast charging occurs at the rated capacity. However, recent empirical studies reveal that the actual charging rate depends on the battery and ambient temperatures and substantially reduces under cold weather. The proposed model is based on a multi-class queuing system where EV classes are determined based on temperature-dependent charger rates. The primary goal is to calculate minimum station capacity that can provide a certain level of quality of service
(QoS) to each customer class. The performance metric describes the percentage of EVs that need to wait for service or leave the station. Case studies are provided to show the relationship between customer arrival rates, charging power and customer classes, and target QoS levels. The results further illustrate that the proposed framework achieves nearly one-third of capacity
savings compared to baseline scenarios. The problems pertinent to temperature effects on EV charging require greater attention as EVs are becoming the main mode of transport in the next decade.
Original languageEnglish
Number of pages6
Publication statusAccepted/In press - 30 Jun 2021
Event56th International Universities Power Engineering Conference - , United Kingdom
Duration: 31 Aug 20213 Sep 2021


Conference56th International Universities Power Engineering Conference
Country/TerritoryUnited Kingdom
Internet address


  • electric vehicles
  • power grid impact
  • battery degradation
  • cold weather
  • queuing system


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