A receding horizon approach to peak power minimization for EV charging stations in the presence of uncertainty

The increasing penetration of plug-in electric vehicles in recent years asks for specific solutions concerning the charging policies to be used in parking lots equipped with charging stations. In fact, simple policies based on uncoordinated charge of vehicles lead, in general, to high peak power demand, which may cause high costs to the car park owner. In this paper, the problem of minimizing the daily peak power of a charging station is addressed. Three sources of uncertainty affect the incoming vehicles: the arrival time, the departure time and the demanded energy to be charged. To assess the quality of the charging service under such uncertainties, a suitable customer satisfaction policy is employed. Depending on the information available on the uncertain variables, two algorithms based on a receding horizon approach are designed. Such algorithms require the solution of linear programs and provide the charging power for each plugged-in vehicle. Numerical simulations are provided to assess performance and computational burden of the algorithms, showing the effectiveness and feasibility of the proposed techniques.

Automated summary

This paper addresses the problem of minimizing the daily peak power of a charging station in parking lots equipped with charging stations for plug-in electric vehicles. Two algorithms are proposed to handle uncertainties, and numerical simulations are provided to demonstrate the effectiveness and feasibility of the techniques.