Analysis and optimisation of electric vehicle charging infrastructure in Turin using a multiple criteria facility location problem approach

Of the many factors hindering the mass adoption of electric vehicles (EVs), the dilemma of charging infrastructure is one of the most difficult to solve. The number of consumers willing to buy an EV are still relatively low. Most consumers are hesitant partially because of the lack in charging infrastructure, yet infrastructure suppliers are wary of large scale investments due to the low number of EV customers. This causality problem is one that is the main focus of this thesis. To begin with, an overview of the problem environment of EV adoption as a whole will be given. This will be followed up by the proposal of a linear programming model aimed at optimising the location of new EV charging infrastructure in the city of Turin (Italy), designed to minimise the total cost of infrastructure upgrades while fulfilling targeted area coverage requirements. The mechanisms contained within the program, as well as inputs, outputs, alterations and different prioritisations are discussed an analysed. The thesis concludes with a set of infrastructure upgrades that could increase the area coverage of the EV charging network in the city of Turin from 62% coverage to 90% coverage at an investment cost of €28,224, with future upgrades to the charging network being required as the number of EVs increases.