Quantification of Adjustable Charging Capacity for EVs Fast-Charging Stations in Urban Transportation Network

As electric vehicle (EV) adoption accelerates, the demand for fast-charging infrastructure, particularly in urban transportation networks, has surged. This growth, however, poses significant challenges to distribution network security due to the high, unpredictable power demands of EV fast-charging stations. This paper proposes a method to quantify the adjustable charging capacity of EV fast-charging stations, focusing on their potential for grid regulation. A modified user equilibrium traffic assignment problem (UE-TAP) model is proposed that considers elastic traffic demands, charging time, and waiting periods to optimize load distribution. Additionally, a capacity-based EV regulation model (C-EVRM) is introduced to directly manage charging loads by imposing capacity limits, minimizing grid risks during peak demand. Using the Pareto frontier theory, we balance user travel costs with station regulatory potential, maximizing both charging experience and grid stability. Case studies on Nanjing’s 37-node system validate the proposed model, demonstrating the effectiveness of this approach in enhancing both grid reliability and user satisfaction.