Optimal Allocation of Electric Vehicle Charging Stations: A case study of the Norwegian road network
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- Master of Science 
Allocating fast charging stations for electric vehicles will be an impor- tant component for ensuring the adoption of electric vehicles. This thesis proposes a framework for ensuring reachability, meaning that all parts of the road network should be accessible with a speci c battery capacity. Two methodologies are tested: (1) a k-Dominating Set with half range, and (2) a Connected k-Dominating Set for ensuring connectivity, both are tested on a dataset representing the Norwegian road network. Distance metrics are measured in kWh for an accurate representation of battery consumption. Tested ranges are 20, 30, and 40 kWh, each tested with k ranging from 1 to 4. The experiment nds that the connected k-dominating set, computed using a greedy algorithm, provides more e cient and desirable solutions than the k-dominating set when applied to this problem. A simple com- parison of the current system and a connected k-dominating set for 20 kWh and k = 2 nds that the current charging station allocation in Norway is not su cient for ensuring reachability with a 20 kWh electric vehicle, and that remote, non- urban areas are especially underrepresented in terms of coverage. Because many parts of the country are already covered, future allocation of fast charging stations should occur in those that currently have low or no coverage in order to stimulate the adoption of electric vehicles.
Masteroppgave(MSc) in Master of Business Analytics - Handelshøyskolen BI, 2021