Planning sustainable hydrogen supply chain infrastructure with uncertain demand

This study introduces a multi-period optimization model taking into account the stochasticity and the effect of uncertainty in the hydrogen production, storage and usage in macro view (e.g. county level). The objective function includes minimization of total daily social cost of the hydrogen supply...

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Bibliographic Details
Published in:International journal of hydrogen energy 2014-04, Vol.39 (13), p.6789-6801
Main Authors: Dayhim, Muhammad, Jafari, Mohsen A., Mazurek, Monica
Format: Article
Language:English
Subjects:
Alternative fuels. Production and utilization
Applied sciences
Automotive engineering
Clean energy in New Jersey
Demand
Electric vehicles
Energy
Exact sciences and technology
Fuels
Hydrogen
Hydrogen storage
Hydrogen supply chain network
Markets
Mathematical models
MILP
Optimization
Spatially aggregated demand
Supply chains
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Summary:This study introduces a multi-period optimization model taking into account the stochasticity and the effect of uncertainty in the hydrogen production, storage and usage in macro view (e.g. county level). The objective function includes minimization of total daily social cost of the hydrogen supply chain network with uncertain demand. There are several factors and key attributes, which influence consumer choice to buy a fuel cell vehicle. At the same time, consumer preference on the demand side is the most important factor in predicting changes in the auto market. A spatially aggregated demand model was developed to estimate the potential demand for fuel cell vehicles based on different household attributes such as income, education etc. These models were applied to evaluate the future hydrogen supply chain for State of New Jersey. •Minimized the total cost of the hydrogen supply network with uncertain demand.•A spatially aggregated demand model was developed to estimate the potential demand.•These models were applied to evaluate the future hydrogen for State of New Jersey.•Hydrogen cost per kg decreases over entire planning horizon.
ISSN:0360-3199
1879-3487
DOI:10.1016/j.ijhydene.2014.02.132