Energy:
Energy:
Analyzing the potential for expanding (public) charging infrastructure
thuega_Aktiengesellschaft_4c

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 800 additional geo-data sources.

THU_1_small

The basis for our analysis is a geographic area of interest. You don’t need to provide any data.

THU_2_small

The forecasting model calculates the expected utilization rate of charging infrastructure using 800 features reflecting the spatial environment.

THU_3_small

Geospin identifies the optimal locations for a demand-driven charging infrastructure.

What customers say:

„Currently, charging infrastructure is barely utilized, so every additional percentage point of usage is crucial!“

Sergej Stimeier, Referent Unternehmensstrategie, ESWE Versorgungs AG

Contact:

Philipp Behrends

pbehrends@geospin.de
0761 59514 615
Geospin GmbH

Freiburg office (company seat):
Kartäuserstraße 39a
D – 79102 Freiburg i. Br.

Contact:
Phone: +49 (0) 40 3092 2303

eMail: info@geospin.de

E-Mail