Evaluation of electric vehicle penetration in a residential sector under demand response considering both cost and convenience

Abstract

This paper proposes a residential load prediction model and an optimal control algorithm considering both electricity payment and waiting time to study impacts of electric vehicle (EV) penetration on the power system. EVs present both challenges (large electrical load) and opportunities (high efficiency and environmentally friendly). The proposed load prediction model simulates heterogeneous residential power consumption. A convex optimization model with real-time pricing (RTP) prediction is proposed to schedule EV charging to determine a tradeoff between electricity payment and waiting time. The dissatisfaction factor from delaying the EV charging, the EV penetration levels and flexibility of charging period are evaluated. The PAPR, standard deviation and electricity payment are significantly decreased by using the proposed optimal control model. Simulation results provide users a base line in which a “best” dissatisfaction factor value can be determined to find a trade-off. This study also shows that, although more and more controlled EV charging has the potential to improve the reliability of the power system, the restricted charging period at the residential sector can be a bottleneck when the EV penetration exceeds a certain level.