A Simulation Framework for Urban Electric Mobility Based on Limited Widespread Data and Spatial Information

Electric Vehicles (EVs) provide an alternative to traditional mobility and a sustainable means of transportation. As a result, electric vehicle sales are increasing across Europe, prompting researchers to wonder about the impact of EVs on smart grids. The proposed framework simulates users' activities, highly characterising individual behaviour using Time Use Survey (TUS) data to estimate EV usage and consumption. Then, for each trip, the routes between origin and destination are determined, simulating in separate modules i) the driving behaviour, ii) the motion of the EV and its discharge considering spatial data and iii) the charge considering users' preference. Thanks to the spatial information openly available, it is possible to characterise the simulation and improve EV consumption estimation. Different scenarios are analysed to demonstrate the versatility of the proposed framework by exploiting its modularity. The individuals' heterogeneity is considered by using an agent-oriented approach. Furthermore, the simulation proceeds on a time-step basis to enable the use of the simulator in a co-simulation environment for future purposes, such as the integration of power networks. The results indicate that achieving a high realism with limited, i.e. containing scarce data for the problem under study, is feasible, enabling researchers to make informed decisions about future mobility.