Planning sustainable hydrogen supply chain infrastructure with uncertain demand

Muhammad Dayhim, Mohsen Jafari, Monica Mazurek

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)6789-6801
Number of pages13
JournalInternational Journal of Hydrogen Energy
Volume39
Issue number13
DOIs
StatePublished - Apr 24 2014

Fingerprint

Supply chains
planning
Planning
Hydrogen
fuel cells
Fuel cells
vehicles
hydrogen
income
optimization
hydrogen production
Hydrogen production
Macros
education
Education
costs
estimates
Costs
Uncertainty

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Condensed Matter Physics
  • Energy Engineering and Power Technology

Keywords

  • Clean energy in New Jersey
  • Hydrogen supply chain network
  • MILP
  • Spatially aggregated demand

Cite this

@article{0f1be16f2fe84802a29dcb0c7f431b28,
title = "Planning sustainable hydrogen supply chain infrastructure with uncertain demand",
abstract = "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.",
keywords = "Clean energy in New Jersey, Hydrogen supply chain network, MILP, Spatially aggregated demand",
author = "Muhammad Dayhim and Mohsen Jafari and Monica Mazurek",
year = "2014",
month = "4",
day = "24",
doi = "10.1016/j.ijhydene.2014.02.132",
language = "English (US)",
volume = "39",
pages = "6789--6801",
journal = "International Journal of Hydrogen Energy",
issn = "0360-3199",
publisher = "Elsevier Limited",
number = "13",

}

Planning sustainable hydrogen supply chain infrastructure with uncertain demand. / Dayhim, Muhammad; Jafari, Mohsen; Mazurek, Monica.

In: International Journal of Hydrogen Energy, Vol. 39, No. 13, 24.04.2014, p. 6789-6801.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Planning sustainable hydrogen supply chain infrastructure with uncertain demand

AU - Dayhim, Muhammad

AU - Jafari, Mohsen

AU - Mazurek, Monica

PY - 2014/4/24

Y1 - 2014/4/24

N2 - 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.

AB - 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.

KW - Clean energy in New Jersey

KW - Hydrogen supply chain network

KW - MILP

KW - Spatially aggregated demand

UR - http://www.scopus.com/inward/record.url?scp=84897986804&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84897986804&partnerID=8YFLogxK

U2 - 10.1016/j.ijhydene.2014.02.132

DO - 10.1016/j.ijhydene.2014.02.132

M3 - Article

AN - SCOPUS:84897986804

VL - 39

SP - 6789

EP - 6801

JO - International Journal of Hydrogen Energy

JF - International Journal of Hydrogen Energy

SN - 0360-3199

IS - 13

ER -