A multiobjective analysis of the potential of scheduling electrical vehicle charging for flattening the duck curve

In this paper, we investigate the demand-flexibility of large-collections of electric vehicles (EVs) by scheduling their demand to flatten the electricity duck curve that emerge as a result of growing solar power production. The scheduling problem is investigated in a bi-objective setting and an additional objective function related to the amount of charge provided to EVs is also analyzed. The first objective is the minimization of the ramp-up requirements of the system. The second objective reflects the quality of service and the potential level of charging station's profit margins. An important characteristics of the proposed model is the effect of total charging capacity on the two objective functions. The analysis is carried out based on a quadratic programming model which is used to calculate the Pareto Front of the two objective functions. This is done through a case study based on real-world data for EV driver behavior, solar generation, and energy consumption. The computational experiments show that there is a high level of competition between these two objectives. Moreover, the effect of different maximal charging capacities on these objectives is observed.