Optimal Multi-Modal Transportation and Electric Power Flow: The Value of Coordinated Dynamic Operation
Jiajie Qiu, Dakota Thompson, Kamal Youcef-Toumi, Amro M. Farid
TL;DR
This work addresses the challenge of coordinating electrified transportation with power grids by introducing OMTEPF, a mesoscopic, time-expanded optimization framework built on hetero-functional graph theory. The approach jointly optimizes five ITES operations (vehicle dispatch, route choice, charging-station queueing, coordinated charging, and vehicle-to-grid stabilization) and enforces an IV-ACOPF power layer to guarantee globally optimal electricity subproblems. Key contributions include a complete TEN-specific specialization of the HFNCF framework, a detailed test-case with realistic topologies and charging modalities, and a rigorous comparison of coordinated versus uncoordinated TEN operation showing a notable but case-dependent 3.6% improvement in performance and improved grid reliability. The findings demonstrate the practical potential of coordinated TEN operation for peak shaving, queue reduction, and feasible grid operation, while outlining scalable research directions and algorithmic needs for city-scale deployment.
Abstract
The electrification of transportation represents a critical challenge in the global transition toward net-zero emissions, as the sector often accounts for more than one-quarter of national energy consumption. Achieving this transformation requires not only widespread adoption of electric vehicles (EVs) but also their seamless integration into interdependent infrastructure systems-specifically, the transportation-electricity nexus (TEN). This paper develops an optimal multi-modal transportation and electric power flow (OMTEPF) model to evaluate the benefits of coordinated, dynamic system operation. Building on recent advances in hetero-functional graph theory, the framework enables joint optimization of five key operational decisions in intelligent TEN management: vehicle dispatch, route choice, charging station queuing, coordinated charging, and vehicle-to-grid stabilization. The mesoscopic, dynamic model explicitly represents individual EVs and their state-of-charge trajectories, thereby extending beyond the prevailing literature's focus on static, macroscopic traffic assignment. It further captures the full scope of the TEN as a system-of-systems, incorporating five distinct charging modalities: private residential, private commercial, wired public commercial, inductive public, and discharging. On the power system side, an IV-ACOPF formulation ensures globally optimal solutions to the electrical subproblems. Comparative analysis demonstrates the substantial value of coordinated TEN operation relative to the status quo of siloed, uncoordinated infrastructure management. This work provides both a novel methodological contribution and actionable insights for the co-design and operation of next-generation sustainable mobility-energy systems.