IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt9b8424mf.html
   My bibliography  Save this paper

Estimating Hydrogen Demand Distribution Using Geographic Information Systems (GIS)

Author

Listed:
  • Ni, Jason
  • Johnson, Nils
  • Ogden, Joan M
  • Yang, Christopher
  • Johnson, Joshua

Abstract

Presented at the National Hydrogen Association Annual Hydrogen Conference (NHA 2005), Washington, DC, March 29 - April 1, 2005 Understanding the evolution of a hydrogen fuel delivery infrastructure depends on the spatial characteristics of the hydrogen demand. We have developed a GIS-based method to model the magnitude and spatial distribution of hydrogen demand based on exogenously-derived market penetration rates and population data. This approach is applied to a study of the state of Ohio, but can be applied to any region of interest. Our methodology is based upon population density, which is mapped at the census-block level and used to calculate hydrogen demand density based on per-capita vehicle ownership, projections for daily hydrogen use per vehicle, and market penetration levels or profiles. Various methods (including buffers and thresholds) are used to identify and aggregate high demand density areas into demand clusters, since only those areas with sufficient hydrogen demand are assumed to be viable locations for refueling stations. The resulting demand clusters (or demand centers) represent the potential areas in which investment in hydrogen infrastructure may be warranted and can be fed into a supply infrastructure model. Sensitivity analyses were conducted to test the impact on hydrogen demand of different market penetration levels, thresholds, and buffer sizes. (i.e. different scenarios) The results allow one to examine the tradeoff between meeting hydrogen demand and the associated projected infrastructure costs. Although this demand model contains many simplifying assumptions, it provides a means for identifying potentially viable locations for hydrogen infrastructure investment at various scenarios.

Suggested Citation

  • Ni, Jason & Johnson, Nils & Ogden, Joan M & Yang, Christopher & Johnson, Joshua, 2005. "Estimating Hydrogen Demand Distribution Using Geographic Information Systems (GIS)," Institute of Transportation Studies, Working Paper Series qt9b8424mf, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt9b8424mf
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/9b8424mf.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Parker, Nathan, 2007. "Optimizing the Design of Biomass Hydrogen Supply ChainsUsing Real-World Spatial Distributions: A Case Study Using California Rice Straw," Institute of Transportation Studies, Working Paper Series qt5kr728sp, Institute of Transportation Studies, UC Davis.
    2. Ogden, Joan M & Johnson, Nils & Yang, Christopher & Ni, Jason & Lin, Zhenhong & Figueroa, José & Johnson, Joshua, 2005. "Conceptual Design of a Fossil Hydrogen Infrastructure with Capture and Sequestration of Carbon Dioxide: Case Study in Ohio," Institute of Transportation Studies, Working Paper Series qt33k8g9wm, Institute of Transportation Studies, UC Davis.
    3. Parker, Nathan C. & Ogden, Joan M. & Fan, Yueyue, 2008. "The role of biomass in California's hydrogen economy," Energy Policy, Elsevier, vol. 36(10), pages 3925-3939, October.
    4. Johnson, Nils & Yang, Christopher & Ni, Jason & Johnson, Joshua & Lin, Zhenhong & Ogden, Joan M, 2005. "Optimal Design of a Fossil Fuel-Based Hydrogen Infrastructure with Carbon Capture and Sequestration: Case Study in Ohio," Institute of Transportation Studies, Working Paper Series qt1t4846kh, Institute of Transportation Studies, UC Davis.
    5. Liu, Jian, 2012. "Electric vehicle charging infrastructure assignment and power grid impacts assessment in Beijing," Energy Policy, Elsevier, vol. 51(C), pages 544-557.
    6. Parker, Nathan C, 2007. "Optimizing the Design of Biomass Hydrogen Supply Chains Using Real-World Spatial Distributions: A Case Study Using California Rice Straw," Institute of Transportation Studies, Working Paper Series qt8sp9n37c, Institute of Transportation Studies, UC Davis.
    7. López Cascales, J.J. & Juan-Segovia, M.C. & Ibáñez Molina, J. & Sánchez Vera, J. & Vivo Vivo, P.M., 2015. "Environmental impact associated with the substitution of internal combustion vehicles by fuel cell vehicles refueled with hydrogen generated by electrolysis using the power grid. An estimation focused," Renewable Energy, Elsevier, vol. 77(C), pages 79-85.
    8. Yang, Christopher & Nicholas, Michael A & Ogden, Joan M, 2006. "Comparison of Idealized and Real-World City Station Citing Models for Hydrogen Distribution," Institute of Transportation Studies, Working Paper Series qt06p1q3z3, Institute of Transportation Studies, UC Davis.
    9. Miller, Marshall PhD & Weinert, Jonathan & Nicholas, Michael, 2006. "Clean Hydrogen for Transportation Applications: Report," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1m26d1p1, Institute of Transportation Studies, UC Berkeley.
    10. Muratori, Matteo & Jadun, Paige & Bush, Brian & Bielen, David & Vimmerstedt, Laura & Gonder, Jeff & Gearhart, Chris & Arent, Doug, 2020. "Future integrated mobility-energy systems: A modeling perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    11. Yueyue Fan & Allen Lee & Nathan Parkerf & Daniel Scheitrum & Amy Myers Jaffe & Rosa Dominguez-Faus & Kenneth Medlock III, 2017. "Geospatial, Temporal and Economic Analysis of Alternative Fuel Infrastructure: The Case of Freight and U.S. Natural Gas Markets," The Energy Journal, , vol. 38(6), pages 199-230, November.
    12. Yueyue Fan & Allen Lee & Nathan Parker & Daniel Scheitrum & Rosa Dominguez-Faus & Amy Myers Jaffe & Kenneth Medlock III, 2017. "Geospatial, Temporal and Economic Analysis of Alternative Fuel Infrastructure: The case of freight and U.S. natural gas markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 6).

    More about this item

    Keywords

    Engineering; UCD-ITS-RP-05-10;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsdav:qt9b8424mf. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.