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A model based on stochastic dynamic programming for determining China's optimal strategic petroleum reserve policy

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  • Zhang, Xiao-Bing
  • Fan, Ying
  • Wei, Yi-Ming

Abstract

China's Strategic Petroleum Reserve (SPR) is currently being prepared. But how large the optimal stockpile size for China should be, what the best acquisition strategies are, how to release the reserve if a disruption occurs, and other related issues still need to be studied in detail. In this paper, we develop a stochastic dynamic programming model based on a total potential cost function of establishing SPRs to evaluate the optimal SPR policy for China. Using this model, empirical results are presented for the optimal size of China's SPR and the best acquisition and drawdown strategies for a few specific cases. The results show that with comprehensive consideration, the optimal SPR size for China is around 320 million barrels. This size is equivalent to about 90 days of net oil import amount in 2006 and should be reached in the year 2017, three years earlier than the national goal, which implies that the need for China to fill the SPR is probably more pressing; the best stockpile release action in a disruption is related to the disruption levels and expected continuation probabilities. The information provided by the results will be useful for decision makers.

Suggested Citation

  • Zhang, Xiao-Bing & Fan, Ying & Wei, Yi-Ming, 2009. "A model based on stochastic dynamic programming for determining China's optimal strategic petroleum reserve policy," Energy Policy, Elsevier, vol. 37(11), pages 4397-4406, November.
  • Handle: RePEc:eee:enepol:v:37:y:2009:i:11:p:4397-4406
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ma, Linwei & Fu, Feng & Li, Zheng & Liu, Pei, 2012. "Oil development in China: Current status and future trends," Energy Policy, Elsevier, vol. 45(C), pages 43-53.
    2. Huanan Li & Xin Chen, 2016. "Dynamic game analysis on China’s public and private oil stockpiles," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 84(1), pages 715-723, October.
    3. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2017. "Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 1-26.
    4. 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.
    5. 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.
    6. Nikolaos Antonakakis & Ioannis Chatziantoniou & George Filis, 2014. "Dynamic Spillovers of Oil Price Shocks and Policy Uncertainty," Department of Economics Working Papers wuwp166, Vienna University of Economics and Business, Department of Economics.
    7. Leung, Guy C.K. & Cherp, Aleh & Jewell, Jessica & Wei, Yi-Ming, 2014. "Securitization of energy supply chains in China," Applied Energy, Elsevier, vol. 123(C), pages 316-326.
    8. Bai, Y. & Zhou, D.Q. & Zhou, P., 2012. "Modelling and analysis of oil import tariff and stockpile policies for coping with supply disruptions," Applied Energy, Elsevier, vol. 97(C), pages 84-90.
    9. 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.
    10. Antonakakis, Nikolaos & Chatziantoniou, Ioannis & Filis, George, 2014. "Spillovers between oil and stock markets at times of geopolitical unrest and economic turbulence," MPRA Paper 59760, University Library of Munich, Germany.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Wu, Gang & Wei, Yi-Ming & Nielsen, Chris & Lu, Xi & McElroy, Michael B., 2012. "A dynamic programming model of China's strategic petroleum reserve: General strategy and the effect of emergencies," Energy Economics, Elsevier, vol. 34(4), pages 1234-1243.
    16. Zhang, Xiao-Bing, 2014. "Optimal strategic oil stockpiling and import tariffs: The case of China," Energy Economics, Elsevier, vol. 45(C), pages 463-474.
    17. Zhao, Chunfu & Chen, Bin, 2014. "China’s oil security from the supply chain perspective: A review," Applied Energy, Elsevier, vol. 136(C), pages 269-279.
    18. Cheng, Ching-Tsung & Lo, Shang-Lien & Lin, Tyrone T., 2011. "Applying real options analysis to assess cleaner energy development strategies," Energy Policy, Elsevier, vol. 39(10), pages 5929-5938, October.
    19. 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.

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