What makes a good public EV charging station? A revealed preference study

TL;DR

The study develops revealed-preference, node-based discrete choice models for predicting intracity EV charging station usage and integrates them into network-design optimization. By estimating MNL and mixed logit models with panel effects from a Montreal RP dataset and enriching them with OpenStreetMap amenities, the authors show distance to stations and proximity to home, along with station outlets, as key usage drivers, while amenities exhibit heterogeneous effects. The work demonstrates that panel effects are essential to accurately capture user heterogeneity and that MXL-based demand representations lead to higher-quality optimization solutions across various scenarios. This RP-based approach provides actionable guidance for siting Level 2 and Level 3 charging stations and offers a robust foundation for future intercity extensions and price-inclusive modeling in EV charging networks.

Abstract

To determine the optimal locations for electric vehicle charging stations, optimisation models need to predict which charging stations users will select. We estimate discrete choice models to predict the usage of charging stations using only readily available information for charging network operators. Our parameter values are estimated from a unique, revealed preferences dataset of charging sessions in Montreal, Quebec. We find that user distance to stations, proximity to home areas, and the number of outlets at each station are significant factors for predicting station usage. Additionally, amenities near charging stations have a neutral effect overall, with some users demonstrating strong preference or aversion for these locations. High variability among the preferences of users highlight the importance of models which incorporate panel effects. Moreover, integrating mixed logit models within the optimization of charging station network design yields high-quality solutions, even when evaluated under other model specifications.

Figures (19)

• Figure 1: Number of total members, by date and account type.
• Figure 2: Number of sessions, by date and account type. The narrow red lines indicate the excluded period for the COVID 19 pandemic.
• Figure 3: Public charging stations within the Island of Montreal.
• Figure 4: Solution (opened and closed stations) for each type of utility.
• Figure 5: Distribution of duration of charging, by level of charging outlet.