新发展格局下的能源安全:基于能源贸易网络的竞争与冲击分析
Energy Security in the New Development Pattern: Competition and Impact Analysis Based on Energy Trade Network
DOI: 10.12677/SA.2023.121017, PDF,   
作者: 张 翔:云南财经大学统计与数学学院,云南 昆明
关键词: 能源网络竞争供应危机风险传播Energy Networks Competition Supply Crisis Spreading of Risk
摘要: 伴随新冠疫情在全球爆发和俄乌战争局势的影响,国际能源市场的不确定性和不稳定性加剧,国家能源安全问题变得和粮食安全同等重要,特别是中国在双循环新发展格局下和“双碳”目标能源战略下保证自身能源安全的供应是值得关注的问题,除了风险预警机制的构建,将中国放在国际能源贸易体系中进行分析则更加的全面。基于贸易竞争和冲击双重角度,通过国际贸易网络建模方法构造煤炭、石油、天然气一次能源的贸易网络,利用网络指标计算两两国家之间的贸易竞争强度,分析了各国在能源贸易竞争网络中的作用以及各国之间的竞争关系,结果发现中国在石油进口竞争中一直处于主导地位;再用以能源消耗量为判定因素的Bootstrap模型仿真能源供应危机在国家间的动态传播过程,利用该模型并计算影响和脆弱程度指标来检测潜在的能源贸易风险,并观察能源贸易参与者在风险传递过程中的角色,只有个别重要出口国家作为风险源才能对现有能源贸易网络产生重大影响,从而表现出全球能源贸易网络呈现“稳健又脆弱”的特征,同时揭示了中国在煤炭、石油、天然气中尽管不是主要出口国,但作为能源贸易网络上的枢纽都有着一定的影响力,由于中国能源贸易模式多样性从而有着很高的抵御能源供应冲击的能力。因此,对其他易受风险冲击的其他能源进口国来说,如何制定合理能源贸易政策保证本国能源安全是亟待解决的问题。
Abstract: With the impact of the global outbreak of COVID-19 and the Russia-Ukraine conflict, the uncertainty and instability of the international energy market have intensified, and national energy security has become as important as food security. In particular, it is worth paying attention to China to ensure its own energy security supply under the new dual-cycle development pattern and the “dual- carbon” target energy strategy. In addition to the construction of risk early warning mechanism, the analysis of China in the international energy trading system is more comprehensive. Based on the dual perspectives of trade competition and impact, this paper constructs the primary energy trade network of coal, oil and natural gas through the modeling method of international trade network, calculates the intensity of trade competition between two countries by using the network index, analyzes the role of each country in the energy trade competition network and the competition relationship between countries. The results show that China has been in the leading position in the competition of oil import. Then, the Bootstrap model with energy consumption as the determining factor was used to simulate the dynamic transmission process of energy supply crisis between countries, and the model was used to calculate the impact and vulnerability indicators to detect potential energy trade risks, and to observe the role of energy trade participants in the risk transmission process. Only a few important exporting countries as risk sources can have a significant impact on the existing energy trade network, which shows that the global energy trade network presents the characteristics of “steady and fragile”. Meanwhile, it reveals that although China is not a major exporter of coal, oil and natural gas, it has a certain influence as the hub of the energy trade network. China is highly resilient to energy supply shocks because of its diverse energy trade patterns. Therefore, for other energy importing countries that are vulnerable to risk shocks, how to formulate reasonable energy trade policies to ensure their own energy security is an urgent problem to be solved.
文章引用:张翔. 新发展格局下的能源安全:基于能源贸易网络的竞争与冲击分析[J]. 统计学与应用, 2023, 12(1): 146-163. https://doi.org/10.12677/SA.2023.121017

参考文献

[1] De Benedictis, L. and Tajoli, L. (2011) The World Trade Network. World Economy, 34, 1417-1454.
[Google Scholar] [CrossRef
[2] Xi, X., Zhou, J., Gao, X., et al. (2019) Impact of Changes in Crude Oil Trade Network Patterns on National Economy. Energy Economics, 84, Article ID: 104490.
[Google Scholar] [CrossRef
[3] Yang, Y., Poonet, J.P.H., Liu, Y. and Bagchi-Sen, S. (2015) Small and Flat Worlds: A Complex Network Analysis of International Trade in Crude Oil. Energy, 93, 534-543.
[Google Scholar] [CrossRef
[4] Wang, W., Li, Z. and Cheng, X. (2019) Evolution of the Global Coal Trade Network: A Complex Network Analysis. Resources Policy, 62, 496-506.
[Google Scholar] [CrossRef
[5] Geng, J.-B., Ji, Q. and Fan, Y. (2014) A Dynamic Analysis on Global Natural Gas Trade Network. Applied Energy, 132, 23-33.
[Google Scholar] [CrossRef
[6] Lee, K.-M., Yang, J.-S., Kim, G., Lee, J., Goh, K.-I. and Kim, I.-M. (2011) Impact of the Topology of Global Macroeconomic Network on the Spreading of Economic Crises. PLOS ONE, 6, e18443.
[Google Scholar] [CrossRef] [PubMed]
[7] Cheewatrakoolpong, K. and Manprasert, S. (2014) Trade Linkages and Crisis Spillovers. Asian Economic Papers, 13, 84-103.
[Google Scholar] [CrossRef
[8] Klimek, P., Obersteiner, M. and Thurner, S. (2015) Systemic Trade-Risk of Critical Resources. Science Advances, 1, e1500522.
[Google Scholar] [CrossRef] [PubMed]
[9] 任素婷, 崔雪锋, 樊瑛. 国际贸易网络中的靴襻渗流模型[J]. 电子科技大学学报, 2015, 44(2): 178-182.
[10] Ying, F., Ren, S., Cai, H. and Cui, X. (2014) The State’s Role and Position in International Trade: A Complex Network Perspective. Economic Modelling, 39, 71-81.
[Google Scholar] [CrossRef
[11] Ruediger, M. (2014) The 1973 Oil Crisis and the Designing of a Danish Energy Policy. Historical Social Research, 39, 94-112.
[12] Tuerk, H. (2014) The Oil Crisis of 1973 as a Challenge to Multilateral Energy Cooperation among Western Industrialized Countries. Historical Social Research, 39, 209-230.
[13] Wei, N., Xie, W.-J. and Zhou, W.-X. (2021) Robustness of the International Oil Trade Network under Targeted Attacks to Economies. Energy, 251, Article ID: 123939.
[Google Scholar] [CrossRef
[14] Du, R., Wang, Y., Dong, G., et al. (2017) A Complex Network Perspective on Interrelations and Evolution Features of International Oil Trade, 2002-2013. Applied Energy, 196, 142-151.
[Google Scholar] [CrossRef
[15] Ball, F., Sirl, D. and Trapman, P. (2010) Analysis of a Stochastic SIR Epidemic on a Random Network Incorporating Household Structure. Mathematical Biosciences, 224, 53-73.
[Google Scholar] [CrossRef] [PubMed]
[16] Wang, C., Huang, X., Hu, X., et al. (2021) Trade Characteristics, Competition Patterns and COVID-19 Related Shock Propagation in the Global Solar Photovoltaic Cell Trade. Applied Energy, 290, Article ID: 116744.
[Google Scholar] [CrossRef
[17] Baxter, G.J., Dorogovtsev, S.N., Goltsev, A.V. and Mendes, J.F.F. (2010) Bootstrap Percolation on Complex Networks. Physical Review E, 82, Article ID: 011103.
[Google Scholar] [CrossRef
[18] Goltsev, A.V., Dorogovtsev, S.N. and Mendes, J.F.F. (2010) k-Core (Bootstrap) Percolation on Complex Networks: Critical Phenomena and Nonlocal Effects. Physical Review E, 73, Article ID: 056101.
[Google Scholar] [CrossRef
[19] Tlusty, T. and Eckmann, J.P. (2009) Remarks on Bootstrap Percolation in Metric Networks. Journal of Physics A: Mathematical and Theoretical, 42, 769-778.
[Google Scholar] [CrossRef
[20] 万宝惠, 张鹏, 张晶, 狄增如, 樊瑛. 二分网上的靴襻渗流[J]. 物理学报, 2012, 61(16): 369-374.
[21] Chen, Z., An, H., An, F., Guan, Q. and Hao, X. (2018) Structural Risk Evaluation of Global Gas Trade by a Network- Based Dynamics Simulation Model. Energy, 159, 457-471.
[Google Scholar] [CrossRef
[22] Newman, M.E.J. (2003) The Structure and Function of Complex Networks. SIAM Review, 45, 167-256.
[Google Scholar] [CrossRef
[23] Glick, R. and Rose, A.K. (1999) Contagion and Trade: Why Are Currency Crises Regional? Journal of International Money and Finance, 18, 603-617.
[Google Scholar] [CrossRef