Modeling Public Charging Infrastructure Considering Points of Interest and Parking Potentials

Abstract. Considering climate change, it is essential to reduceCO2 emissions. The provision of charging infrastructure in publicspaces for electromobility – along with the substitution of conventionalpower generation by renewable energies – can contribute to the energytransition in the transport sector. Scenarios for the spatial distributionof this charging infrastructure can help to exemplify the need for chargingpoints and their impact, for example on power grids. We model two kinds of demand for public charging infrastructure. First, wemodel the demand for public charging points to compensate for the lack ofhome charging points, which is derived from a previously developed andpublished model addressing electric-vehicle ownership (with and without homecharging options) in households. Second, and in the focus of the workpresented here, is the demand for public charging infrastructure at pointsof interest (POIs). Their locations are derived from OpenStreetMap (OSM)data and weighted based on an evaluation of movement profiles from theMobilität in Deutschland survey (MiD, German for “Mobility inGermany”). We combine those two demands with the available parking spacesand generate distributions for possible future charging points. We use araster-based approach in which all vector data are rasterized andcomputations are performed on a municipality's full grid. The presentedapplication area is Wiesbaden, and the methodology is generally applicableto municipalities in Germany. The model is compared with three other models or model variants in acorrelation comparison in order to determine the influence of certain modelassumptions and input data. The identification of potential charging pointsin public spaces plays an important role in modeling the future energysystem – especially the power grid – as the rapid adoption of electricvehicles will shift locations of electrical demand. With our investigation,we would like to present a new method to simulate future public chargingpoint locations and show the influences of different modeling methods.