Analysis of the electric vehicle charging station coverage in an Italian alpine region - D. Bacilieri; M. Ciolli; P. Zatelli (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences)
The transition towards more sustainable transport promotes the adoption of electric vehicles, and the status of the charging infrastructure is a crucial point to achieve this result. This research examines the availability of EV charging stations in the Provincia Autonoma di Trento (PAT), a popular tourist destination in the Italian eastern Alps. The study uses the Open Charge Map dataset, which is representative of the distribution and density of charging stations and is available under the Creative Commons Attribution 4.0 (CC-BY 4.0) International license. The road network and charging stations are combined, and the distance between roads and potential users is evaluated. Custom software has been developed and released under the GNU GPL license for the network analysis for this research, while all the carthographic processing has been carried out in QGIS. The mean distance of any point on the road network to the closest charging point is 4763.4 m, with a standard deviation of 4601.6 m. The maximum distance is 36766.6 m, with a minimum distance of 0 m. The density of charging stations is evaluated by extracting charging points for each municipality. The average number of charging stations per municipality is 1.9, with 42.4% having no charging points and 56.6% having at least one. With respect to resident population, the average number of charging points is 0.84 per 1000 inhabitants, with a standard deviation of 1.39. The results are compatible with with the recent Italian national report MOTUS-E and are useful for future EV charging infrastructure planning. In conclusion, results highlight that in our study area the charging stations reach the maximum density per inhabitant in touristic locations. From the point of view of data availability, the research highlighted that the quality of Open Data sources like Open Charge Map should be improved to obtain more reliable results.