Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices. (15th October 2020) - Zhou, Kaile; Cheng, Lexin; Lu, Xinhui; Wen, Lulu
Highlights: Two optimal scheduling models of electric vehicles (EVs) charging are proposed. The degradation cost and parking fee are considered in the costs of two methods. Recommendation model considers inconvenience of EV owners in the costs. Recommendation model can help EV owners reduce charging time and save costs. Performance of models are compared in different charging patterns and EV scales. Abstract: The electric vehicle (EV) industry has developed rapidly in the past decade, and the number of EVs has surged. When large scale EVs are connected to the power grid, the peak load of the power grid surges during the rush time of EV charging. The uncoordinated large scale of EV charging is harmful to the operation of the power system. Hence, dynamic pricing mechanisms have been proposed that use cost reduction as the motivation for EV owners to alter certain charging decisions. In this study, two optimal scheduling models for the charging of EVs, basic scheduling and recommendation models, are proposed to achieve cost minimization for EV owners in response to dynamic pricing. The basic scheduling model schedules the charging and discharging behaviours of EVs based on the connection and disconnection times of the EVs to the power grid. The costs involved in this model include the charging cost, discharging reward, degradation cost of EV battery, and parking fee. Based on the basic scheduling model, the proposed recommendation model recommends that the EV owner leave earlier to save on the parking fee, which may inconvenience the EV owner. This inconvenience is further considered in the costs, by measuring the coefficient of inconvenience to represent the time sensitivity of the EV owner. Finally, the comparison results of charging and discharging behaviours and the corresponding costs based on the two optimal scheduling models are sent to the EV owners. This can help EV owners, who have different degrees of sensitivity to time, to make optimal charging decisions. Moreover, the recommendation model can improve the utilization efficiency of charging facilities and relieve the pressure on them in the scheduling process when EVs are connected to the power grid on a large scale.