Coordinating Urban Power-Traffic Networks: A Subsidy-Based Nash–Stackelberg–Nash Game Model

The growing penetration of electric vehicles results in interdependence between power and transportation networks, in which the coordination among drivers and network operators is highly desirable for raising the respective benefits. Considering the self-interest behavior of each entity, this article develops a Nash–Stackelberg–Nash game framework to model their noncooperative interactions. Specifically, the upper level power and transportation system operators determine monetary incentives independently to achieve the respective economic-emission dispatch, while each lower level driver reacts to the incentive and makes route/charging choice to minimize his own travel cost. To mitigate the upper bounding issue in the existing tariff-based incentive scheme (i.e., the upper bound of the tariff needs to be specified manually), we propose a subsidy-based method to evoke the self-discipline of the upper level operators and to facilitate public acceptance. The bilevel model is transformed into two single-level subproblems through the Karush–Kuhn–Tucker conditions, and a Gauss–Seidel iterative algorithm is developed to identify an operational equilibrium. Numerical experiments demonstrate the performance of the noncooperative operation and the efficacy of the subsidy-based scheme by comparing them with the cooperative operation and the tariff-based scheme, respectively.