Predicting Demand for Hydrogen Station Fueling

Jennifer Kurtz, Thomas Bradley, Erin Winkler, Chris Gearhart

Research output: Contribution to journalArticlepeer-review

34 Scopus Citations


Full function hydrogen stations are a reality; fuel cell electric vehicle drivers can pull up to commercial fueling stations and receive 3–5 kg in less than 5 min, for an approximately 300-mile range. The demand for hydrogen is increasing, driven by an increase in the fueling of public and private fuel cell vehicles. This study describes the development and value of a model that simulates stochastic future demand at a hydrogen filling station. The predictive hydrogen demand model described in this article is trained from mathematical models constructed from actual hydrogen fill count, amount, and frequency data. Future fill probabilities inform the hour-by-hour demand profile and the station state of either “available, ready to fill” or “available, filling”. For example, a prediction for a station generally dispensing 5,000 kg a week on a Friday afternoon at 4 p.m. is 16 fills, totaling 48.7 kg, with a 0.52 proportion of time spent in “available, filling” state yielding 31 min of filling time. This is a first-of-its kind, published study on predicting future hydrogen demand by the time of day (e.g., hour-by-hour intervals) and day of week. This study can be used for hydrogen station requirements and operation and maintenance strategies and to assess the impact of demand variations and scenarios. This article presents the current status of hydrogen demand, the model development methods, a set of sample results. Discussion and conclusions concentrate on the value and use of the proposed model.

Original languageAmerican English
Pages (from-to)32298-32310
Number of pages13
JournalInternational Journal of Hydrogen Energy
Issue number56
StatePublished - 13 Nov 2020

Bibliographical note

Publisher Copyright:
© 2019 Hydrogen Energy Publications LLC

NREL Publication Number

  • NREL/JA-5400-73651


  • Demand
  • Fill profile
  • Hydrogen
  • Prediction
  • Station


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