Optimal Pricing of Public Electric Vehicle Charging Stations Considering Operations of Coupled Transportation and Power Systems

Recognized as an efficient approach to reduce fossil fuel consumption and alleviate environment crisis, the adoption of electric vehicles (EVs) in urban transportation system is receiving more and more attention. EVs will tightly couple the operations of urban transportation network (UTN) and power distribution network (PDN), necessitating the interdependent traffic-power modeling to optimize the on-road EV charging decisions. In this article, the optimal charging pricing problem of public electric vehicle charging stations (EVCSs) considering the interdependent operations of UTN and PDN is modeled from the view of the charging network operator (CNO), which is formulated as a bi-level optimization problem. In order to match the spatial size of UTN and power capacity of PDN, multiple PDNs are incorporated in the modeling to support EVCSs at different parts of UTN, permitting charging load migration across PDNs. Fixed point theory is used to analyze properties of the CNO's optimal charging pricing problem. An iterative method is designed to obtain the optimal charging pricing result, which solves the CNO's pricing subproblem and PDN market clearing subproblem in turn. Numerical case study results validate the effectiveness of proposed models and methods, and demonstrate the impacts of the CNO pricing on the operations of UTN and PDN.

I. Introduction

The massive adoption of electric vehicles (EVs) in urban transportation system is widely regarded as an important approach to reduce greenhouse gas emission and alleviate environmental pollution [1]. EV deployment is closely connected with the operations of power distribution network (PDN) and urban transportation network (UTN). On the one hand, high EV penetration rate means large energy fulfillment demand, posing great pressure on PDN security and reliability [2]. On the other hand, due to the intrinsic traveling characteristic differences between EVs and gasoline vehicles (GVs), the substitution of GVs with EVs in UTN will inevitably change traffic flow patterns and may induce potential risk that does not exist in traditional UTN conditions [3]. Besides, both PDN and UTN can also influence EV’s applicability and popularity through adjusting power capacity offered and charging fees, respectively. In one word, due to the tight interactions between EVs and PDN/UTN, optimal operation of charging facilities for large-scale on-road EVs needs interdependent traffic-power modeling.