Methodology for an optimal deployment of the recharging infrastructure for electric vehicles

Abstract

184 p. CO2 emissions must be reduced to meet the international commitments to tackle climate change. One of the most promising alternatives for such reduction is the electrification of transport, especially in urban environments, due to its advantages in terms of lack of local emissions and noise reduction. Yet, the lack of publicly accessible charging infrastructure is preventing the mass-adoption of electro-mobility. EV customers want to see a dense enough publicly accessible charging infrastructure network, but they will seldom use it if they can use private home charging. Hence, the economic feasibility of deploying such charging infrastructure must be carefully assessed. Although there have been several attempts to assess the economic performance of operating publicly accessible charging infrastructure, none of them if able to handle the complexity of electro-mobility (by e.g. merging all different charging alternatives into the same analysis). This thesis aims at filling the identified gap, by defining a new methodology which looks at the whole value chain, is business-oriented, performs a quantitative analysis, compares EV against ICE vehicles and takes into account the relationships between the different charging alternatives into a single assessment. The three main contributions of the thesis are: 1) The new methodology extends the scope for analysing complex business cases to consider the different dimensions of the business case at the same time, 2) This new methodology highlights the crucial need to involve appropriate representatives of the relevant stakeholders (decision-makers) in the analysis from the very beginning of the process, and 3) The new methodology has an oriented, tailored approach from the early stages of the analysis to obtain significant results which increase the reliability of the outcomes and guide the decision-making process.

Original document

The different versions of the original document can be found in:

• http://hdl.handle.net/10810/41408