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Optimal path for China's strategic petroleum reserve: A dynamic programming analysis

Author

Listed:
  • Bai, Y.
  • Zhou, D.Q.
  • Zhou, P.
  • Zhang, L.B.

Abstract

This paper proposes a dynamic programming model to explore the optimal stockpiling path for China's strategic petroleum reserve before 2020. The optimal oil acquisition sizes in 2008–2020 under different scenarios are estimated. The effects of oil price, risks and elasticity value on inventory size are further investigated. It is found that the optimal stockpile acquisition strategies are mainly determined by oil price and total inventory costs. While oil supply disruption is not considered, China's optimal stockpile acquisition rate increases from 19.2 to 52million barrels from 2008 to 2020. If an oil supply disruption occurs, the oil acquisition rate will be reduced significantly. However, it may not be a good strategy to interrupt oil reserve activities in order to minimize the total costs for the entire planning period.

Suggested Citation

  • Bai, Y. & Zhou, D.Q. & Zhou, P. & Zhang, L.B., 2012. "Optimal path for China's strategic petroleum reserve: A dynamic programming analysis," Energy Economics, Elsevier, vol. 34(4), pages 1058-1063.
  • Handle: RePEc:eee:eneeco:v:34:y:2012:i:4:p:1058-1063
    DOI: 10.1016/j.eneco.2011.08.019
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    References listed on IDEAS

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    Cited by:

    1. Tavana, Madjid & Behzadian, Majid & Pirdashti, Mohsen & Pirdashti, Hasan, 2013. "A PROMETHEE-GDSS for oil and gas pipeline planning in the Caspian Sea basin," Energy Economics, Elsevier, vol. 36(C), pages 716-728.
    2. Murphy, Frederic & Oliveira, Fernando S., 2013. "Pricing option contracts on the strategic petroleum reserve," Energy Economics, Elsevier, vol. 40(C), pages 242-250.
    3. Zhang, Xiao-Bing & Qin, Ping & Chen, Xiaolan, 2017. "Strategic oil stockpiling for energy security: The case of China and India," Energy Economics, Elsevier, vol. 61(C), pages 253-260.
    4. Xie, Nan & Yan, Zhijun & Zhou, Yi & Huang, Wenjun, 2017. "China's optimal stockpiling policies in the context of new oil price trend," Energy Policy, Elsevier, vol. 105(C), pages 332-340.
    5. Bai, Y. & Dahl, C.A. & Zhou, D.Q. & Zhou, P., 2014. "Stockpile strategy for China׳s emergency oil reserve: A dynamic programming approach," Energy Policy, Elsevier, vol. 73(C), pages 12-20.
    6. Bai, Yang & Zhou, Peng & Tian, Lixin & Meng, Fanyi, 2016. "Desirable Strategic Petroleum Reserves policies in response to supply uncertainty: A stochastic analysis," Applied Energy, Elsevier, vol. 162(C), pages 1523-1529.
    7. Lu, Ze-Yu & Li, Wen-Hua & Xie, Bai-Chen & Shang, Li-Feng, 2015. "Study on China’s wind power development path—Based on the target for 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 197-208.
    8. Chen, Xin & Mu, Hailin & Li, Huanan & Gui, Shusen, 2014. "Using stockpile delegation to improve China׳s strategic oil policy: A multi-dimension stochastic dynamic programming approach," Energy Policy, Elsevier, vol. 69(C), pages 28-42.
    9. Jiao, Jian-Ling & Han, Kuang-Yi & Wu, Gang & Li, Lan-Lan & Wei, Yi-Ming, 2014. "The effect of an SPR on the oil price in China: A system dynamics approach," Applied Energy, Elsevier, vol. 133(C), pages 363-373.
    10. Zhang, Xiao-Bing, 2014. "Optimal strategic oil stockpiling and import tariffs: The case of China," Energy Economics, Elsevier, vol. 45(C), pages 463-474.

    More about this item

    Keywords

    Strategic petroleum reserve; Dynamic programming; Petroleum acquisition strategy; Stockpile;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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