Decentralized vs. Centralized Scheduling of Electric Vehicle Routing and Power Distribution in Coupled Electricity-Mobility Networks

The integration of electric mobility into smart grids is among the most effective strategies to combat climate change and promote sustainable transportation. However, this transition introduces several operational and coordination challenges. This study compares three short-term operation scheduling approaches for integrated transportation networks (TN) and electricity distribution networks (EDN), aiming to assess the impact of different electric mobility routing strategies on both EDN performance and vehicle owner outcomes. A second-order cone programming (SOCP) model is employed using benchmark EDN and TN configurations. The examined scenarios include: (i) uncoordinated scheduling (no coordination between EDN and TN, resembling conventional TN operation), (ii) centralized scheduling (a single operator manages both TN and EDN to maximize social welfare), and (iii) decentralized scheduling using the ADMM algorithm with localized nodal pricing to provide economic incentives for grid-aware EV charging behavior (distinct operators manage TN and EDN with separate objectives). The results indicate that uncoordinated scheduling leads to the highest operational costs (11.7% higher). The coordinated decentralized framework achieves reduced traffic latency (3.6% lower than the centralized approach) at the expense of slightly increased operational costs (0.96% higher).