Abstract
In this work we address the efficient operation of public charging stations. Matching energy supply and demand requires an interdisciplinary understanding of both the mobility of electric vehicle (EV) users and the load balancing mechanisms. As a result of existing mobility studies, we propose in this work a routing service for searching and reserving public charging spots in the neighborhood of a given destination. When comparing the search results for direct drive with those for a multimodal route (using driving, walking and public transport) in an urban environment, we obtain for the latter significantly more charging options in particular at low e-mobility penetration levels, at a cost of slightly longer trip duration. Further contributions address the schedule optimization, that, due to the proposed distributed architecture, can be performed independently at each public charging station. We formulate an integer program for the controlled charging and compare results obtained both with the exact and with a greedy heuristic method.