Flexibility potential of electric vehicle charging: A trip chain analysis under bi-criterion stochastic dynamic user equilibrium

The widespread adoption of electric vehicles (EVs) creates opportunities to use EV charging load as a flexible resource to improve grid operation. In urban areas, EV users typically follow trip chains in their daily travel, offering temporal and spatial flexibility in EV charging. Specifically, charging at slow-charging spots at trip destinations is temporally flexible when the parking duration exceeds the required charging time. In contrast, charging at fast charging stations (FCSs) during trips is spatially flexible, with route and FCS choice influenced by traffic congestion, FCS charging prices, and user perception. In this paper, we propose a bi-criterion stochastic dynamic user equilibrium (SDUE) model with trip chain demand, which captures route and FCS choice of EV users and derives fast and slow charging loads. The model accounts for user response to traffic congestion and FCS charging prices, along with the randomness in user perception of trip utility. A quantitative evaluation is also presented on the spatial flexibility of fast charging driven by price incentives, and the temporal flexibility of slow charging enabled by long parking durations. A case study in Sioux Falls is conducted to evaluate the flexibility potential of EV charging, revealing that reduced randomness in user perception enhances the spatial flexibility potential of fast charging. Additionally, the temporal flexibility potential of slow charging varies across location types, such as home, work, and other locations, depending on arrival times and parking durations. This research provides key insights for optimizing grid management and enhancing EV integration into power systems. • A quantitative evaluation of EV charging flexibility to power grids is presented. • A bi-criterion stochastic dynamic user equilibrium model is proposed. • Users respond to traffic congestion and charging prices with perception randomness. • Spatial flexibility is enhanced by reduced user perception randomness. • Temporal flexibility is dependent on user arrival times and parking durations.