Two-stage stochastic sizing and packetized energy scheduling of BEV charging stations with quality of service constraints. (15th February 2020) - Graber, Giuseppe; Calderaro, Vito; Mancarella, Pierluigi; Galdi, Vincenzo
Highlights: A method to size charging stations and schedule charging times of EV is presented. 200.000 observed real parking events at the University of Salerno are analyzed. A packetized energy approach allows for solving the charging scheduling problem. The solution ensures a high QoS level and minimize the cost for the CS manager. Method and results are useful to study the potential of V2G applications. Abstract: The expected deployment of battery electric vehicles (BEVs) strongly depends on the development of an adequate charging station (CS) infrastructure that guarantees a certain level of quality of service (QoS) to the BEV users. This paper proposes a two-stage method to select the number and type of CSs in parking areas (PAs) and schedule the charging sessions of the incoming BEVs ensuring a predetermined QoS level while minimizing the cost for the CS manager. In particular, stage one solves the CS sizing problem while stage two involves a probabilistic simulation procedure able to solve the charging scheduling problem by using a packetized energy approach. We also take into account the typical charging current and voltage characteristic of a BEV battery pack, and the real statistical distribution of BEV arriving times and expected parking times. A case study based on the PA at the University of Salerno Campus is used to demonstrate the effectiveness of the proposed method.