Estimation of charging demand for electric vehicles by discrete choice models and numerical simulations: Application to a case study in Turin

Abstract

ABSTRACT: The electrification of vehicles is considered one of the most important strategies for addressing the issues related to energy dependence and climate change. To meet user needs, electric vehicle (EV) management for charging operations is essential. This study uses modelling and simulation of EV user behaviour to forecast possible scenarios for electric charging in cities and to identify potential management problems and opportunities for improvement of EVs and EV charging infrastructures. The conurbation of Turin was selected as a case study to reproduce realistic scenarios by applying discrete choice modelling based on socio-economic and transport system data. One of objectives of the study was to describe user charging behaviour from a geographic perspective to model where users prefer to charge in the area studied according to the variables that may affect decisions. Another objective was to estimate the number of electric vehicles in Turin and the characteristics of their users, both of which are helpful in understanding electric mobility within a city. Analysing these behavioural issues in a modelling framework can provide a set of tools to compare and evaluate a variety of possible modifications, indicating an adequate network of charging infrastructure to facilitate the diffusion of electric vehicles.

Keywords

• Electric vehicles
• Charging demand
• Charging stations
• Discrete choice models
• User preference