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THE ELECTRIC VEHICLE CHARGING STATION LOCATION PROBLEM: A PARKING-BASED ASSIGNMENT METHOD FOR SEATTLE

Access to electric vehicle (EV) charging stations will impact EV adoption rates, use decisions, electrified mile shares, petroleum demand, and power consumption across times of day. This work uses parking information from over 30,000 personal-trip records in the Puget Sound Regional Council’s 2006 household travel survey to determine public (non-residential) parking locations and durations. Regression equations predict parking demand variables (total vehicle-hours per zone/neighborhood and parked-time per vehicle-trip) as a function of site accessibility, local jobs and population densities, trip attributes, and other variables available in most regions and travel surveys. Several of these variables are key inputs for a mixed integer programming problem, developed here for optimal EV-charging-station location assignments. The algorithm minimizes EV users’ station access costs while penalizing unmet demand. This useful specification was used to determine top locations for installing a constrained number of charging stations within 10 miles of Seattle’s downtown, showing how charging location schemes’ access costs respond to parking demand and station locations. The models developed here are generalizable to data sets available for most any region, and can be used to make more informed decisions on station locations around the world.