Capacity Optimization of EV Charging Networks: A Greedy Algorithmic Approach

In the recent years, there has been a steady increase in the use of electrical vehicles (EV). Their further adoption is becoming more dependent on the quality of service provided by the charging infrastructure. In this paper, the focus is on optimizing the charging infrastructure from the point of minimizing the service drop modelled using the standard M/M/c/c loss queue. To be exact, a mathematical model is proposed for the problem of optimizing capacities at individual stations in an EV charging network. The novelty is in considering the relation of capacity of a charging station to its arrival rate. Due to the non-linearity of the problem, a greedy algorithm combined with a local search is developed for finding near optimal configurations of the system. The new model is evaluated using real-world data for population density and existing charging infrastructure for metropolitan areas. The conducted computational experiments, show that charging networks optimized using the proposed model, significantly better reflect the state-on-the-ground than standardly used models, while maintaining a low service drop rate.