Predicting demand for hydrogen station fueling. (13th November 2020)

• Record Type: Journal Article
• Authors: Kurtz, Jennifer; Bradley, Thomas; Winkler, Erin; Gearhart, Chris
• Is Part Of: International journal of hydrogen energy. Volume 45:Number 56(2020)
• Page Start: 32298
• Page End: 32310
• Publication Date: 2020-11-13
• Subjects: Hydrogen -- Demand -- Station -- Prediction -- Fill profile; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2019.10.014
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: 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. Highlights: Global demand for hydrogen for vehicles is higher than ever before. Fuel cell vehicle deployment is expected to drive increased demand for hydrogen. Future hydrogen demand is typically estimated in bulk or on long time frames. Measured hydrogen and gas fill trends are the basis of an hour-by-hour demand model. This model could guide station development and operation.