IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v133y2017icp424-442.html
   My bibliography  Save this article

A three-stage stochastic programming method for LNG supply system infrastructure development and inventory routing in demanding countries

Author

Listed:
  • Zhang, Haoran
  • Liang, Yongtu
  • Liao, Qi
  • Yan, Xiaohan
  • Shen, Yun
  • Zhao, Yabin

Abstract

Despite of the high demand for liquefied natural gas (LNG) in demanding countries, an ideal means for establishing the LNG supply system has not yet been found in many regions. In this paper, a three-stage stochastic programming method has been proposed for LNG supply system infrastructure development and inventory routing in demanding countries. The minimum daily cost is set as the objective function; and the cost consists of the delivery cost, liquefaction cost, purchase cost, and construction cost. Under the constraints of delivery mode, volume, vehicle, time, and infrastructure construction, a multi-scenario MILP model was established and solved by a hybrid computational method (ACO-MILP), and the optimal infrastructure development and inventory routing were presented as the result. Finally, the method was successfully applied to the LNG supply system along the Yangtze River in China. Furthermore, compared with the other methods, the superiority of the method was verified.

Suggested Citation

  • Zhang, Haoran & Liang, Yongtu & Liao, Qi & Yan, Xiaohan & Shen, Yun & Zhao, Yabin, 2017. "A three-stage stochastic programming method for LNG supply system infrastructure development and inventory routing in demanding countries," Energy, Elsevier, vol. 133(C), pages 424-442.
    • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:424-442
    DOI: 10.1016/j.energy.2017.05.090
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217308459
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.05.090?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Long, Yin & Yoshida, Yoshikuni & Meng, Jing & Guan, Dabo & Yao, Liming & Zhang, Haoran, 2019. "Unequal age-based household emission and its monthly variation embodied in energy consumption – A cases study of Tokyo, Japan," Applied Energy, Elsevier, vol. 247(C), pages 350-362.
    2. Wang, Bohong & Klemeš, Jiří Jaromír & Liang, Yongtu & Yuan, Meng & Zhang, Haoran & Liu, Jiayi, 2020. "Implementing hydrogen injection in coal-dominated regions: Supply chain optimisation and reliability analysis," Energy, Elsevier, vol. 201(C).
    3. Zhigang Duan & Yamin Yan & Xiaohan Yan & Qi Liao & Wan Zhang & Yongtu Liang & Tianqi Xia, 2017. "An MILP Method for Design of Distributed Energy Resource System Considering Stochastic Energy Supply and Demand," Energies, MDPI, vol. 11(1), pages 1-23, December.
    4. Long, Yin & Yoshida, Yoshikuni & Fang, Kai & Zhang, Haoran & Dhondt, Maya, 2019. "City-level household carbon footprint from purchaser point of view by a modified input-output model," Applied Energy, Elsevier, vol. 236(C), pages 379-387.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:133:y:2017:i:c:p:424-442. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.