Marginal charging station pricing in an intelligent electric transportation system

We consider the coupling introduced between power and transportation systems through Electric Vehicles (EVs). We envision that a number of charging network operators track the mobility of EVs to better estimate their battery charging needs. They use this information to make better-informed decisions on how to participate in the wholesale market of electricity and also to design marginal retail prices that reduce wait times and electricity costs at charging stations. To formulate these decision-making and price design problems, we introduce a network flow model that can capture the temporally-variable travel and charge patterns of an EV population through expanding the transportation network with virtual arcs.