Impacts of vehicle electrification on large-scale transportation and charging infrastructure: A dynamic network modeling approach

Abstract

The rise in penetration of electric vehicles (EV) presents new challenges for infrastructure management due to the intertwining of the transportation system with the electric power system through charging infrastructure. The integration of EVs into the transportation network requires a dynamic transportation network modeling approach that considers the impacts of EV charging. Existing studies often suffer from drawbacks such as static traffic models, limited network size, and unrealistic assumptions about traffic demand and EV behavior. The study proposes a holistic framework that incorporates essential components related to EVs such as charging stations, EV charging routing, charging behavior, and energy consumption, into a dynamic traffic model for large-scale networks. The framework is applied to a large-scale transportation network in the Central Ohio region. The high granularity dynamic traffic model is calibrated with real-world traffic data and vehicle registration data, resulting in more accurate estimations of traffic flow and energy consumption. Based on the calibrated model, different scenarios are analyzed and the results reveal spatiotemporal variations in the utilization of the charging station and the patterns of neighborhood electricity consumption. Furthermore, the study analyzes the impacts of the EV penetration ratio, the roadside charging ratio, the coverage ratio of the fast charging station on the energy consumption across the network, the emission of greenhouse gases, and the waiting times at the charging stations. The proposed flexible framework provides a foundation for future studies to refine submodels and explore the interdependency between traffic and electric power systems more comprehensively.