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LNG market liberalization and LNG transportation: Evaluation based on fleet size and composition model

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  • Yuan, Jun
  • Shi, Xunpeng
  • He, Junliang

Abstract

The proportion of spot trading and short-term contracts has gradually increased in the rapidly growing LNG market, leading to more uncertainties in LNG demand and prices that significantly challenge LNG shipping decisions. In this paper, a mathematical model is developed to minimize transportation costs from multiple exporting countries to multiple importing countries under demand and price uncertainty, both of which are results of LNG market liberalization. A Gaussian process metamodel based simulation optimization method is proposed to solve the fleet planning problem, accounting for various uncertainties. A case study is given to illustrate the effects of uncertainties on the optimal solutions. The results demonstrate that shipping companies may purchase fewer ships and charter more ships to hedge against the risk of uncertainty. LNG market liberalization can significantly reduce its transportation costs and carbon emissions. The results suggest the need for further LNG market liberalization and measures to mitigate uncertainties for shipping companies, such as removing destination clauses.

Suggested Citation

  • Yuan, Jun & Shi, Xunpeng & He, Junliang, 2024. "LNG market liberalization and LNG transportation: Evaluation based on fleet size and composition model," Applied Energy, Elsevier, vol. 358(C).
    • Handle: RePEc:eee:appene:v:358:y:2024:i:c:s0306261924000400
    DOI: 10.1016/j.apenergy.2024.122657
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    as
    1. Jang, Hayoung & Jeong, Byongug & Zhou, Peilin & Ha, Seungman & Nam, Dong, 2021. "Demystifying the lifecycle environmental benefits and harms of LNG as marine fuel," Applied Energy, Elsevier, vol. 292(C).
    2. Liu, Shuguang & Huang, Weilai & Ma, Huiming, 2009. "An effective genetic algorithm for the fleet size and mix vehicle routing problems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(3), pages 434-445, May.
    3. D. Huang & T. Allen & W. Notz & N. Zeng, 2006. "Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models," Journal of Global Optimization, Springer, vol. 34(3), pages 441-466, March.
    4. Kristin Uggen & Marte Fodstad & Vibeke Nørstebø, 2013. "Using and extending fix-and-relax to solve maritime inventory routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(2), pages 355-377, July.
    5. Shi, Xunpeng & Shen, Yifan, 2021. "Macroeconomic uncertainty and natural gas prices: Revisiting the Asian Premium," Energy Economics, Elsevier, vol. 94(C).
    6. Dawei Zhan & Huanlai Xing, 2020. "Expected improvement for expensive optimization: a review," Journal of Global Optimization, Springer, vol. 78(3), pages 507-544, November.
    7. Jokinen, Raine & Pettersson, Frank & Saxén, Henrik, 2015. "An MILP model for optimization of a small-scale LNG supply chain along a coastline," Applied Energy, Elsevier, vol. 138(C), pages 423-431.
    8. Shi, Xunpeng & Padinjare Variam, Hari Malamakkavu, 2016. "Gas and LNG trading hubs, hub indexation and destination flexibility in East Asia," Energy Policy, Elsevier, vol. 96(C), pages 587-596.
    9. Koza, David Franz & Ropke, Stefan & Boleda Molas, Anna, 2017. "The liquefied natural gas infrastructure and tanker fleet sizing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 99(C), pages 96-114.
    10. Sun, Lijun & Zhang, Yuankai & Hu, Xiangpei, 2021. "Economical-traveling-distance-based fleet composition with fuel costs: An application in petrol distribution," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 147(C).
    11. Qiang Meng & Tingsong Wang, 2010. "A chance constrained programming model for short-term liner ship fleet planning problems," Maritime Policy & Management, Taylor & Francis Journals, vol. 37(4), pages 329-346, July.
    12. Salhi, Said & Wassan, Niaz & Hajarat, Mutaz, 2013. "The Fleet Size and Mix Vehicle Routing Problem with Backhauls: Formulation and Set Partitioning-based Heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 22-35.
    13. Pantuso, Giovanni & Fagerholt, Kjetil & Hvattum, Lars Magnus, 2014. "A survey on maritime fleet size and mix problems," European Journal of Operational Research, Elsevier, vol. 235(2), pages 341-349.
    14. Olmez Turan, Merve & Flamand, Tulay, 2023. "Optimizing investment and transportation decisions for the European natural gas supply chain," Applied Energy, Elsevier, vol. 337(C).
    15. Meng, Qiang & Wang, Tingsong & Wang, Shuaian, 2012. "Short-term liner ship fleet planning with container transshipment and uncertain container shipment demand," European Journal of Operational Research, Elsevier, vol. 223(1), pages 96-105.
    16. Awudu, Iddrisu & Zhang, Jun, 2013. "Stochastic production planning for a biofuel supply chain under demand and price uncertainties," Applied Energy, Elsevier, vol. 103(C), pages 189-196.
    17. Babai, M. Zied & Ivanov, Dmitry & Kwon, Oh Kang, 2023. "Optimal ordering quantity under stochastic time-dependent price and demand with a supply disruption: A solution based on the change of measure technique," Omega, Elsevier, vol. 116(C).
    18. Arslan, Ayşe N. & Papageorgiou, Dimitri J., 2017. "Bulk ship fleet renewal and deployment under uncertainty: A multi-stage stochastic programming approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 69-96.
    19. Haowei Wang & Jun Yuan & Szu Hui Ng, 2020. "Gaussian process based optimization algorithms with input uncertainty," IISE Transactions, Taylor & Francis Journals, vol. 52(4), pages 377-393, April.
    20. Schulte, Benedikt & Sachs, Anna-Lena, 2020. "The price-setting newsvendor with Poisson demand," European Journal of Operational Research, Elsevier, vol. 283(1), pages 125-137.
    21. Wang, Xin & Fagerholt, Kjetil & Wallace, Stein W., 2018. "Planning for charters: A stochastic maritime fleet composition and deployment problem," Omega, Elsevier, vol. 79(C), pages 54-66.
    22. Postali, Fernando A.S. & Picchetti, Paulo, 2006. "Geometric Brownian Motion and structural breaks in oil prices: A quantitative analysis," Energy Economics, Elsevier, vol. 28(4), pages 506-522, July.
    23. Nian, Victor & Yuan, Jun, 2017. "A method for analysis of maritime transportation systems in the life cycle approach – The oil tanker example," Applied Energy, Elsevier, vol. 206(C), pages 1579-1589.
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