LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Node-based vs. path-based location models for urban hydrogen refueling stations: Comparing convenience and coverage abilities

Photo from wikipedia

Abstract For optimizing locations of hydrogen refueling stations, two popular approaches represent fuel demands as either nodes or paths, which imply different refueling behavior and definitions of convenience. This paper… Click to show full abstract

Abstract For optimizing locations of hydrogen refueling stations, two popular approaches represent fuel demands as either nodes or paths, which imply different refueling behavior and definitions of convenience. This paper compares path-based vs. node-based models from the perspective of minimizing total additional travel time and feasibly covering all demands with the same number of stations. For this comparison, two new station location models are introduced that extend the Flow Capturing Location Model (FCLM) and p-Median Problem (PMP) by consistently defining upper limits on vehicle driving range and maximum inconvenience on refueling trips. Results for an idealized metropolitan area and Orlando, Florida show that path-based refueling substantially reduces wasteful travel time for refueling and covers more demand feasibly and more equitably in most scenarios. Path-based models incorporate the fact that residents of a zone regularly interact with other zones; therefore, individual stations can cover flows originating both near and far from their locations. This study suggests that path-based approaches to planning hydrogen refueling infrastructure enable more people in more neighborhoods to refuel fuel-cell vehicles without wasting excessive time or running out of fuel.

Keywords: path based; hydrogen; location; refueling stations; hydrogen refueling

Journal Title: International Journal of Hydrogen Energy
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.