Bi-Objective Power-Traffic Pricing Coordination: Incorporating User Choice Stochasticity

The population of electric vehicles and fast charging stations has created stronger interdependency between the operation of urban traffic networks and power distribution networks. Congestion tolls and charging prices are effective leverages of the two network operators to influence the drivers' routing and charging decisions and “indirectly” regulate the resulting charging loads and vehicular flows. In this paper, a two-stage power-traffic pricing framework incorporating both the multi-goal pricing and user choice stochasticity is established. In the first stage, the optimal power-traffic flow distribution is determined by the Nash bargain model. In the second stage, the prices are optimized to guide the drivers' behaviors to achieve the desired network flow pattern, where the discrete choice model is employed to describe the user decision stochasticity. Case studies demonstrate the effectiveness of the proposed framework and methods.