For humanity to tackle the challenges of climate change, the transportation sector will need to undergo major changes and reforms over the coming years. Electric vehicles (EVs) have long been recognized as an important part of the solution to decreasing our dependency on limited fossil energy sources, as well as reducing greenhouse gas emissions. Thereby, governments everywhere have started setting ambitious goals for EV adoption for the next few decades. Today's charging infrastructure is, however, not sufficient to service all these new EVs. One reason for this, is the so-called "chicken and egg" problem: private investment is unlikely while the number of electric cars is not big enough to make a potential business profitable, and potential customers are less inclined to invest in electric vehicles while charging infrastructure is not widespread. To break this cycle, it is therefore necessary for a central authority to drive investment in these infrastructures during a first stage, therefore promoting a higher EV adoption. Recent works on optimization problems for siting and/or sizing of charging stations for EVs have started addressing this issue by considering strategic multi-period siting optimization problems. One limitation of these works, however, is that they consider the demand (i.e. number of EVs and their geographical distribution) over time to be static and given as an input.
In this presentation, we present a more holistic optimization framework that considers how new infrastructure impacts EV demand growth, and how the infrastructure can be installed in a way that it properly responds to future demand. This framework has been validated by Hydro-Québec and is being applied to help achieve Quebec's objective of having 100,000 EVs on the roads by 2020, and 1,000,000 by 2030.
This is a joint work with Miguel Anjos and Bernard Gendron (CIRRELT).
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