Anticipatory planning for equitable and productive curbside electric vehicle charging stations

Abstract

Two challenges to planning public electric vehicle (EV) charging networks remain in U.S. cities, including uneven productivity of charging stations and inequitable charging access across user groups. The unpredictable EV market penetration over the long term further complicates the relevant infrastructure planning. However, the extant planning approaches are limited in addressing both challenges simultaneously when considering future uncertainties. Therefore, we propose a data-driven anticipatory framework to plan for EV charging station allocation near urban amenities based on charging-while-parking behavioral patterns. We focus on two user groups, i.e., multi-family and single-family residents. We compare the productivity-equity outcomes of allocation scenarios under three planning strategies and four possible ratios between both user groups. The framework addresses the incremental charging demands at different market levels for each scenario. An in-depth case study of Alachua County, FL, shows that over-emphasizing multi-family charging demands when placing EV charging stations may undermine their overall productivity. We then suggest three pathways to balance equitable access and optimized productivity for the community based on the comparison of planning scenarios. The proposed framework is generalizable to other EV-initiating communities. This study sheds light on future-oriented adaptive planning for transportation infrastructure during the energy transition.