부산대학교 도서관

The growing prevalence of electric vehicles (EVs) enhances the coupling of urban transportation networks (UTNs) and power distribution networks (PDNs). First, based on the inverse optimization (IO), this article proposes a holistic pricing framework to manage the power-traffic flows at network equilibrium (NE) toward the least-cost social optimum (SO) state with minimum extra user charges. Second, a coordinated operation model is proposed which assigns the traffic flows and schedules the power generation within grid operation and EV routing and charging constraints. It removes some unrealistic assumptions in existing works. Third, a novel decentralized bi-level decomposition algorithm is designed. It efficiently tackles the computation intractability and preserves the network data privacy by decoupling the UTN and PDN problems in the outer layer and adaptively generating operation results-aware optimal charging paths in the inner layer. Finally, real-world UTN-based case studies validate the effectiveness of the proposed method and specify the economic and operational merits of aligning the costly and congested NE with the economic and efficient SO. The model can reduce the total operation cost by 4.2% and renewable power spillage by 11.7%. Based on the framework, model, and results in this article, an IO-based pricing is proposed in our sequel paper.