Electric vehicles state of charge and spatial distribution forecasting: A high-resolution model

In the near future Electrical Vehicless (EVs) will most likely replace conventional combustion-engine based ones. This and the increase in the use of renewable energy sources will have an important positive impact on our ecosystem. At the same time it will require a serious reanalysis and possibly redesign of the structure of our distribution network. In this paper we propose a model that, at a relatively fine level, describes the behavior of communities in terms of transport requirements, derives statistic driving behavior patterns and determines the corresponding induced Electric Vehicle Charging habits. The energy consumption of every simulated EV is computed taking into account the features of the trip and the vehicle itself. The model has been tailored to data extracted from a portion of the Milan (Italy) metropolitan area, but is trivially adaptable to any area for which a similar set of data is available. The obtained results are compared to data from similar works, showing good agreement. The outputs of the model, i.e. the energy consumption of the vehicles and their time-spatial distribution within a specific area (and consequently the loads on the distribution network nodes due to charging operations), have been (and will be) used to perform impact analyses on network performances and on personal mobility.