Placement and Sizing of EV Charging Stations According to Centrality of the Underlying Network

Abstract

EV placement and sizing are the subject of ever increasing studies in the last decade mostly relying on optimization approaches. This study looks at the EV network as a complex network where the nodes are the potential locations of charging stations (CSs) and edges (links) represent the traffic flow. It then investigates the impacts of some graph properties on the solutions of the CS placement problem. In fact, the graph centrality and its variants are used to find the locations of CSs to reduce the average waiting times at the stations. It is shown that the centrality based analysis can lead to promising results for small and medium EV networks leaving the large networks to be addressed by more complicated approaches. Simulations are performed on the central (downtown) part of Perth City EV network, Western Australia scaled down by the real traffic information.