An Efficient LP-Based Approach for Spatial-Temporal Coordination of Electric Vehicles in Electricity-Transportation Nexus

A growing integration of electric vehicles (EV) and fast charging stations (FCS) has paved the way for the emergence of transportation and power distribution networks. However, previous work on the coordination of EV in the transportation system mainly focuses on static traffic assignment (STA) models which are unable to characterize the temporal evolution of EV flows on traffic links. Meanwhile, limited prior effort in dynamic traffic assignment (DTA) employs a static FCS model which is unable to describe the temporal evolution of charging and discharging (C&D) behavior of EV flows, while respecting the state-of-charge (SoC) related operating constraints, hindering full exploitation of EV flexibility potentials. To bridge the knowledge gap, this paper proposes a novel DTA model to optimize the spatial-temporal distribution of EV flows on roads and at FCSs, taking into account their flexible C&D options and SoC-related constraints, through the solution of only a single linear program. Case studies validate the effectiveness of the proposed DTA model by benchmarking its performance against traditional STA models, and corroborate the core benefits from the proposed spatial-temporal coordination of EV C&D demand in the power distribution network in terms of peak demand reduction, improved RES absorption, reduced carbon emission as well as more efficient network congestion management.