Design and operation of a stochastic hydrogen supply chain network under demand uncertainty

被引:116
|
作者
Almansoori, A. [1 ]
Shah, N. [2 ]
机构
[1] Petr Inst, Dept Chem Engn, Abu Dhabi, U Arab Emirates
[2] Univ London Imperial Coll Sci Technol & Med, Dept Chem Engn, Ctr Proc Syst Engn, London SW7 2AZ, England
关键词
Hydrogen supply chain; MILP stochastic model; Demand uncertainty; Risk analysis; Scenarios-based approach; Great Britain; INFRASTRUCTURE; OPTIMIZATION;
D O I
10.1016/j.ijhydene.2011.11.091
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The design of a future hydrogen supply chain (HSC) network is challenging due to the: (1) involvement of many echelons in the supply chain network, (2) high level of interactions between the supply chain components and sub-systems, and (3) uncertainty in hydrogen demand. Most of the early attempts to design the future HSC failed to incorporate all these challenges in a single generic optimization framework using mathematical modeling approach. Building on our previous multiperiod MILP model, the model presented in this paper is expanded to take into account uncertainty arising from long-term variation in hydrogen demand using a scenario-based approach. The model also adds another echelon: fueling stations and local distribution of hydrogen. Our results show that the future HSC network is somewhat similar to the existing petroleum infrastructure in terms of production, distribution, and storage. In both situations, the most feasible solution is centralized production plants with truck and rail delivery and small-to-large storage facilities. The main difference is that the future hydrogen supply has the benefits of using distributed forecourt production of hydrogen at local fueling stations via several production technologies. Finally, the performance of the studied models was evaluated using sensitivity and risk analyses. Copyright (C) 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:3965 / 3977
页数:13
相关论文
共 50 条
  • [1] A stochastic programming approach for supply chain network design under uncertainty
    Santoso, T
    Ahmed, S
    Goetschalckx, M
    Shapiro, A
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2005, 167 (01) : 96 - 115
  • [2] Optimization of a hydrogen supply chain under demand uncertainty
    Kim, Jiyong
    Lee, Younghee
    Moon, Il
    [J]. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2008, 33 (18) : 4715 - 4729
  • [3] Distribution Supply Chain Design under Demand uncertainty
    Bouzembrak, Yamine
    Allaoui, Hamid
    Goncalves, Gilles
    Bouchriha, Hanen
    [J]. PROCEEDINGS OF INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND SYSTEMS MANAGEMENT (IESM'2011): INNOVATIVE APPROACHES AND TECHNOLOGIES FOR NETWORKED MANUFACTURING ENTERPRISES MANAGEMENT, 2011, : 657 - 665
  • [4] Optimization of a hydrogen supply chain network design under demand uncertainty by multi-objective genetic algorithms
    Robles, Jesus Ochoa
    Azzaro-Pantel, Catherine
    Aguilar-Lasserre, Alberto
    [J]. COMPUTERS & CHEMICAL ENGINEERING, 2020, 140
  • [5] Supply chain network design under uncertainty
    Ji, Xiaoyu
    Zhao, Xiande
    [J]. PROCEEDINGS OF THE 11TH ANNUAL CONFERENCE OF ASIA PACIFIC DECISION SCIENCES INSTITUTE: INNOVATION & SERVICE EXCELLENCE FOR COMPETITIVE ADVANTAGE IN THE GLOBAL ENVIRONMENT, 2006, : 526 - +
  • [6] Modelling medical oxygen supply chain network under demand uncertainty using stochastic programming
    Sawant, Rahul
    Kumar, Anish
    Yadav, Vineet Kumar
    [J]. OPSEARCH, 2024,
  • [7] A responsive closed-loop supply chain network design under demand uncertainty
    Han, Bing
    Shi, Shanshan
    Park, Yongshin
    Xu, Yuan
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2024, 192
  • [8] Closed-Loop Supply Chain Network Design Under Demand and Return Uncertainty
    Uster, Halit
    Hwang, Sung Ook
    [J]. TRANSPORTATION SCIENCE, 2017, 51 (04) : 1063 - 1085
  • [9] Resilient and sustainable semiconductor supply chain network design under trade credit and uncertainty of supply and demand
    Tsao, Yu-Chung
    Balo, Habtamu Tesfaye
    Lee, Carmen Kar Hang
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2024, 274
  • [10] Supply Chain Network Design under Demand Uncertainty and Supply Disruptions: A Distributionally Robust Optimization Approach
    Qiu, Ruozhen
    Wang, Yizhi
    [J]. SCIENTIFIC PROGRAMMING, 2016, 2016