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

For optimizing the locations of hydrogen refueling stations, the two most popular approaches represent the demands for fuel as either nodes or paths, which 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 from the perspective of minimizing total additional travel time and feasibly covering all demands with the same number of stations. For this comparison, the authors 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 degree of inconvenience on refueling trips. The authors compare the models on an idealized metropolitan area. Results show that path-based refueling usually reduces wasteful travel time for refueling and covers more demand feasibly. Assuming path-based behavior, installing a station can cover demands widespread across the region, and the overall coverage pattern is more equitable. 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 an excessive amount of time or running out of fuel.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee ADC80 Standing Committee on Alternative Transportation Fuels and Technologies.
  • Corporate Authors:

    Transportation Research Board

    ,    
  • Authors:
    • Kuby, Michael
    • Honma, Yudai
  • Conference:
  • Date: 2019

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 9p

Subject/Index Terms

Filing Info

  • Accession Number: 01698161
  • Record Type: Publication
  • Report/Paper Numbers: 19-05375
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 7 2018 9:47AM