Multi-criteria optimization of electric vehicle fleet charging and discharging schedule for secondary frequency control

Abstract

Commercial fleet of electric vehicles (EV) is serving clients for different purposes, but each of those services is requiring some time to be fulfilled. When the vehicle is charging or discharging using the vehicle-to-grid (V2G) concept, the waiting time to service increases, and the vehicle owner is suffering losses due to the reduced service quality. In this chapter, we are exploring the scheduling optimization problem of an EV fleet controlled by the aggregator. The optimization of vehicle daily scheduling is needed in order to increase the revenues from offering ancillary services and reduce costs of service quality loss. New, practical multi-criteria decision-making methodologies for the daily scheduling of EV fleet are proposed. Criteria that have to be fulfilled simultaneously are the minimization of the service waiting time (SWT), maximization of the revenues coming from the frequency regulation services and the minimization of the costs incurred by the vehicle charging, including the costs of battery degradation. The stochastic nature of vehicles driving patterns (time the car owner has to calculate for the service provision) is considered using the queuing theory. The proposed methodology has been successfully implemented on two cases of EV commercial fleet daily scheduling.