Dynamic equilibrium of the coupled transportation and power networks considering electric vehicles charging behavior

The coupling between the transportation network (TN) and power distribution network (PDN) is becoming more significant due to the increasing use of electric vehicles (EVs) and fast charging stations (FCSs). Accurately characterizing the dynamic coupling between TN and PDN is crucial. However, existing literature exhibits significant deficiencies in modeling the travel behaviors of gasoline vehicles (GVs) and EVs, as well as the propagation characteristics of mixed traffic networks. Moreover, it overlooks the queuing capacity limits of FCSs and the impact of queue overflow on TN. To address these issues, this study presents a stochastic dynamic user equilibrium (SDUE) modeling framework for coupled networks considering EVs charging behavior. This framework comprehensively captures the dynamic interactions among departure times, path choices, FCS choices, and electricity prices within the TN and PDN. To capture the traffic dynamics, a multi-class traffic flow propagation model for EVs and GVs, considering EV charging behavior, is developed. Additionally, an improved fixed-point algorithm is proposed to obtain the dynamic equilibrium state of the coupled networks. Case studies reveal that reducing FCS capacity degrades overall network performance. Therefore, it is essential to consider queue overflow when devising traffic policies to enhance network performance and assessing the layout of FCSs. Furthermore, the results indicate that the coupled operation strategy, in comparison to independent operation strategies, can reduce total traffic delay costs by 28.4%, decrease average waiting time at FCSs by 28.7%, and lower power losses by 11.7%. These findings underscore the significance of collaborative management and planning of TN and PDN in response to the escalating demand for EVs.