TY - JOUR
T1 - Design of hydrogen supply chains under demand uncertainty - A case study of passenger transport in Germany
AU - Ochoa Bique, Anton
AU - Maia, Leonardo K.K.
AU - Grossmann, Ignacio E.
AU - Zondervan, Edwin
N1 - Publisher Copyright:
© 2021 Walter de Gruyter GmbH, Berlin/Boston 2021.
PY - 2021/8/23
Y1 - 2021/8/23
N2 - A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.
AB - A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.
KW - 2024 OA procedure
KW - fuel infrastructures
KW - hydrogen supply chain design
KW - mixed integer linear programming
KW - stochastic optimization
KW - water electrolysis technology
UR - http://www.scopus.com/inward/record.url?scp=85114407750&partnerID=8YFLogxK
U2 - 10.1515/psr-2020-0052
DO - 10.1515/psr-2020-0052
M3 - Article
AN - SCOPUS:85114407750
SN - 2365-659X
VL - 8
JO - Physical Sciences Reviews
JF - Physical Sciences Reviews
IS - 6
ER -