Coordinated pricing of coupled urban Power-Traffic Networks: The value of information sharing. (1st November 2021) - Sheng, Yujie; Guo, Qinglai; Chen, Feng; Xu, Luo; Zhang, Yang
Highlights: Power-traffic pricing interaction modeled as a multi-leader Stackelberg game. Divergent pricing goals and imperfect information of network operators considered. A decentralized coordinated pricing framework proposed considering privacy issues. Influences of charging electric vehicle penetration and traffic demand discussed. Abstract: The growing demand for the fast charging of electric vehicles has created stronger interdependency between the operation of urban traffic networks and power distribution networks. This paper investigates the necessity and feasible mechanism of coordinated pricing in coupled urban power-traffic networks. The retail charging pricing of the power distribution network operator and congestion pricing of the urban traffic network operator will simultaneously affect the routing and charging decision choices for electric vehicles. Then, the response of multiclass vehicles—i.e., the aggregated traffic flow and charging load—will in return affect the operation performance—i.e., power loss and traffic congestion—of the coupled networks. However, due to operators' differing pricing goals and limited access to user information, the actual response for vehicles might deviate from the respective expectation of the two operators under isolated pricing. With the growing penetration of electric vehicles, such deviation might become more evident, calling for a focus on pricing coordination. To investigate the necessity of coordinated pricing, the Stackelberg game framework is employed to model the pricing interactions between operators (leaders) and vehicles (followers). Accounting for privacy issues, a decentralized coordination framework of the two networks is proposed for information sharing. The numerical test results confirm the negative impacts of isolated pricing and demonstrate the effectiveness of coordinated pricing. Sensitivity analysis is conducted to examine the influence of critical parameters: e.g., charging electric vehicle penetration and total travel demand.