|Start Page Number:||163|
|End Page Number:||181|
|Publication Date:||Jun 2017|
|Authors:||Fernandes Xavier, Rebelo Joana|
|Keywords:||combinatorial optimization, scheduling, programming: dynamic, transportation: road, energy, heuristics, simulation, demand|
In this paper, we study the problem of establishing a dynamic charging schedule of electric vehicles (EVs) at a charging station, assuming that limited power implies that only a limited number of EVs can charge simultaneously. The only control we assume to be available to the charging station is the ability to (at any given time) turn on or off the power supply to any EV, with this tool we want to develop a charging schedule that will satisfy the energy demands of the EVs in their intended deadlines. We propose two distinct approaches to this problem: a discretized time version, based on a greedy‐like algorithm, and a continuous time version, based on linear programming. We compare these two approaches and numerically study the improvement they yield in the efficiency of the charging procedure, when applied to simulated data based on real parking data. Finally, we illustrate the flexibility of the models by sketching several possible extensions.