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Maximum flow-based formulation for the optimal location of electric vehicle charging stations

arXiv 2312.05980 ↗First posted 10 Dec 2023math.OC cs.AIcited by 0

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Abstract (arXiv)

With the increasing effects of climate change, the urgency to step away from fossil fuels is greater than ever before. Electric vehicles (EVs) are one way to diminish these effects, but their widespread adoption is often limited by the insufficient availability of charging stations. In this work, our goal is to expand the infrastructure of EV charging stations, in order to provide a better quality of service in terms of user satisfaction (and availability of charging stations). Specifically, our focus is directed towards urban areas. We first propose a model for the assignment of EV charging demand to stations, framing it as a maximum flow problem. This model is the basis for the evaluation of user satisfaction with a given charging infrastructure. Secondly, we incorporate the maximum flow model into a mixed-integer linear program, where decisions on the opening of new stations and on the expansion of their capacity through additional outlets is accounted for. We showcase our methodology for the city of Montreal, demonstrating the scalability of our approach to handle real-world scenarios. We conclude that considering both spacial and temporal variations in charging demand is meaningful when solving realistic instances.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 44 references that are in the map. First posted on arXiv 10 Dec 2023.

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2 of 44 references.

References · 2

  1. 2022Optimising Electric Vehicle Charging Station Placement using Advanced Discrete Choice Modelscited by 1
  2. 2023Incorporating time-dependent demand patterns in the optimal location of capacitated charging stationscited by 1

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