Unraveling user type characteristics: Towards a taxonomy for charging infrastructure

Abstract

Many European cities with air quality concerns struggle how to further roll out charging infrastructure in the coming years in a cost effective manner. Typical concerns include charging point under-capacity (scarcity of charging points due to high demand) as well as over-capacity (placement of charging points in less prevalent locations). Being able to predict future utilization of charging stations would provide a great deal to policy makers in order to achieve more optimized infrastructure planning and roll out. This paper argues that in order to make solid predictions on the future use of charging stations one needs to acknowledge significant differences in charging behavior amongst user types, be it residents, commuters, city visitors or users of electric car sharing schemes. This paper sets out to unravel the particular charging patterns of different user types in terms of timing, charging amount and location preferences. By combining the specific user patterns with probabilities on which locations these users are likely to charge, the user-based charging patterns provide a powerful starting point to make predictions how charging points are likely to be used, as well as provide policy makers tools to make strategic decisions how to optimize the roll out of new charging infrastructure.