Optimisation of placement of charging stations for electrical vehicles in road networks
Please note that this project is self-funded.
The aim of this project is to develop novel modelling and algorithmic solutions for the optimisation problem by drawing from existing research in the fields of optimisation and network theory.
Due to the ever increasing concern about the environment, the resulting policies and advances in technology, zero and low emission electrical and hybrid vehicles have become much more important and popular.
Despite the advantages of electrical vehicles, their relatively limited cruising range (in comparison to traditional diesel/petrol vehicles) and significant battery loading time provide major challenges for their usage.
As a result, in order for electrical vehicles to be viable, it is necessary to have a sufficient number of charging stations effectively distributed throughout a road network. Given a particular road network layout, determining optimal locations and capacities for these charging stations is a challenging multi-objective optimisation problem with many constraints.
One of the key objectives is to minimise travel time by requiring detours necessary for battery recharging to be as short as possible.
On the other hand, constraints require the number of charging stations to be reasonably small, the distance between neighbouring stations must not exceed the cruising range of electrical vehicles, and capacities of the charging stations should be sufficient enough to avoid bottlenecks.
Project aims and methods
We will examine new mathematical models for the problem and subsequently develop methodologies to provide efficient and effective algorithmic solutions for the mathematical models.
The models are going to be based on different kinds of the facility location problem formulations for networks and graphs, taking into consideration particular types of constraints and objectives appearing in navigation of electrical vehicles.
We hypothesise that this will result in better solutions relative to existing published work especially with regard to scaling more effectively to larger road networks and to deciding on station capacities.
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