Node-Based vs. Path-Based Location Models for Urban Hydrogen Refueling Stations: Comparing Convenience and Coverage Abilities

Authors: Michael Kuby*, Arizona State University, Yudai Honma, University of Tokyo, Institute of Industrial Science
Topics: Transportation Geography, Energy, Spatial Analysis & Modeling
Keywords: Alternative-fuel vehicle, Hydrogen, Fuel cell, Refueling, Infrastructure
Session Type: Paper
Day: 4/3/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Washington 4, Marriott, Exhibition Level
Presentation File: No File Uploaded

For optimizing the locations of refueling stations for alternative fuels such as hydrogen, two popular approaches represent the demands for fuel as either nodes or paths. These contrasting ways of modeling demand imply different refueling behavior by drivers and different definitions of convenience. This paper compares the path-based vs. node-based modeling choice as fairly as possible in terms of minimizing total additional travel time and feasibly covering all demands with the same number of stations. For this comparison, we introduce two new station location models that extend the Flow Capturing Location Model (FCLM) and the p-Median Problem (PMP) by including consistently defined upper limits on vehicle driving range and tolerable level of inconvenience on refueling trips. We compare the models on two networks: an idealized metropolitan area and Orlando, Florida. Results show that path-based refueling substantially reduces wasteful travel time for refueling and covers more demand feasibly in most scenarios. Assuming path-based behavior, individual stations can cover flows originating both locally and non-locally. This study suggests that a path-based approach to planning hydrogen refueling infrastructure is both more efficient and more equitable for drivers, enabling more people in more neighborhoods to adopt and conveniently refuel fuel-cell vehicles without wasting their time excessively or running out of fuel. The findings and models are relevant to other fast-filling alternative-fuel vehicles, such as compressed natural gas, ethanol, or battery switching.

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