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Optimization of China's energy structure based on portfolio theory

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  • Gao, Cuixia
  • Sun, Mei
  • Shen, Bo
  • Li, Ranran
  • Tian, Lixin

Abstract

Facing the mounting pressures of meeting energy and environment needs and reducing its dependence for fossil fuels, China needs to make more effort to develop renewable energy. This paper attempts to use portfolio theory to optimize China's overall energy system with considering the learning curve effect of renewable energy cost and the characteristic of fossil energy cost increasing over time. It also takes into account additional factors such as environmental costs of coal consumption and various growth rates of the cumulative R&D (research and development) capacity for solar power. This research has found that the development of renewable energy in China has tremendous potential but it will not replace fossil energy in the next decades. The sensitivity analysis of this paper indicates that development of solar power is driven not only by the cumulative installed capacity but also by the cumulative R&D capacity.

Suggested Citation

  • Gao, Cuixia & Sun, Mei & Shen, Bo & Li, Ranran & Tian, Lixin, 2014. "Optimization of China's energy structure based on portfolio theory," Energy, Elsevier, vol. 77(C), pages 890-897.
  • Handle: RePEc:eee:energy:v:77:y:2014:i:c:p:890-897
    DOI: 10.1016/j.energy.2014.09.075
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    9. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Antelo, Susana Iglesias & Soares, Isabel, 2017. "Energy planning and modern portfolio theory: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 636-651.
    10. Li, Bing-Bing & Liang, Qiao-Mei & Wang, Jin-Cheng, 2015. "A comparative study on prediction methods for China's medium- and long-term coal demand," Energy, Elsevier, vol. 93(P2), pages 1671-1683.
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    14. Zhang, Shuang & Zhao, Tao & Xie, Bai-Chen, 2018. "What is the optimal power generation mix of China? An empirical analysis using portfolio theory," Applied Energy, Elsevier, vol. 229(C), pages 522-536.
    15. Gao, Cuixia & Su, Bin & Sun, Mei & Zhang, Xiaoling & Zhang, Zhonghua, 2018. "Interprovincial transfer of embodied primary energy in China: A complex network approach," Applied Energy, Elsevier, vol. 215(C), pages 792-807.
    16. Yu-zhuo, Zhang & Xin-gang, Zhao & Ling-zhi, Ren & Ji, Liang & Ping-kuo, Liu, 2017. "The development of China's biomass power industry under feed-in tariff and renewable portfolio standard: A system dynamics analysis," Energy, Elsevier, vol. 139(C), pages 947-961.
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    19. Liyin Shen & Yingli Lou & Yali Huang & Jindao Chen, 2018. "A driving–driven perspective on the key carbon emission sectors in China," 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. 93(1), pages 349-371, August.
    20. Gan, Peck Yean & Li, ZhiDong, 2015. "Quantitative study on long term global solar photovoltaic market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 88-99.
    21. Inzunza, Andrés & Muñoz, Francisco D. & Moreno, Rodrigo, 2021. "Measuring the effects of environmental policies on electricity markets risk," Energy Economics, Elsevier, vol. 102(C).
    22. Ali Nowrouzi & Mostafa Panahi & Hamidreza Ghaffarzadeh & Abtin Ataei, 2019. "Iran’s gas export portfolio risk analysis based on the development of dependency risk framework," Energy & Environment, , vol. 30(4), pages 629-640, June.
    23. Pan, Lingying & Liu, Pei & Li, Zheng, 2017. "A system dynamic analysis of China’s oil supply chain: Over-capacity and energy security issues," Applied Energy, Elsevier, vol. 188(C), pages 508-520.
    24. Anasis, John G. & Khalil, Mohammad Aslam Khan & Butenhoff, Christopher & Bluffstone, Randall & Lendaris, George G., 2019. "Optimal energy resource mix for the US and China to meet emissions pledges," Applied Energy, Elsevier, vol. 238(C), pages 92-100.

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