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

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  • 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
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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).

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