Modelling of the vehicle to grid storage potential considering uncer-tainties in user behavior based on fleet test data

We present data about the mobility behaviour and the storage potential from a 12 month fleet test of 20 battery electric vehicles (Volkswagen- e-up!) equipped with communication technology and a bidirectional charger for providing ancillary services. In this system, the users had to specify their driving needs via a smartphone app. These data have been collected in the context of the lighthouse project INEES (Smart Grid Connection of Electric Vehicles Enabling Ancillary Services). For the minimum battery level we observe a mean value of 47% demonstrating that people are willing to provide storage for vehicle to grid (V2G) services. However, intelligent charging strategies need to consider a high proportion of unpredicted trips (52%) and diverse individual mobility behaviours. The results obtained are of strong relevance for the analysis of the potential of V2G services. Furthermore, a clustering algorithm was performed to compare plug-in with parking times for different user profiles. We introduce a simulation model to calculate the storage potential for larger pools including unpredicted user behaviour. In contrast to previous work, the model allows to investigate the influence of uncertainties in user behaviour and forecasts inaccuracies on the use of storage potential for grid services.