Problem: Attractiveness and acceptance of electric vehicles crucially depends on a public, accessible and exhaustive charging infrastructure. However, the implementation and maintenance of such infrastructure is characterized by high cost and low efficiency. With an average utilization rate of only around 4%, the performance depends on finding the optimal location. A lack of previous experience often complicates the identification of these ideal locations.
Solution: Geospin has developed forecasting models which reliably predict the expected utilizations of charging stations—across all of Germany. Choosing the optimal location is thus straight-forward, for instance by maximizing the utilization rates of your charging infrastructure. The model was trained on several hundred-thousands of charging processes across 2,500 charging points, exploiting over 700 additional geo-data sources.
The basis for our analysis is a geographic area of interest. You don’t need to provide any data.
The forecasting model calculates the expected utilization rate of charging infrastructure using 700 features reflecting the spatial environment.
Geospin identifies the optimal locations for a demand-driven charging infrastructure.
„Currently, charging infrastructure is barely utilized, so every additional percentage point of usage is crucial!“
Sergej Stimeier, Referent Unternehmensstrategie, ESWE Versorgungs AG