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What is the optimal power generation mix of China? An empirical analysis using portfolio theory

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  • Zhang, Shuang
  • Zhao, Tao
  • Xie, Bai-Chen

Abstract

This paper employs portfolio theory to explore China’s optimal power generation mix in 2030, which considers the possibilities of technological developments, and the government’s non-fossil generation and non-hydro renewable generation policy targets. The aim of this paper is to investigate China’s efficient generation portfolios by comparing the portfolio costs, risks, efficient frontiers, and diversification levels under different cases and scenarios. The results show that fossil fuel generation technologies have no advantages when considering the technological restrictions. In addition, various preferences for non-fossil generation technologies are influenced greatly by the goals of pursuing cost or risk minimization and different policy targets. Positive effects exist for a non-fossil generation goal or a policy target package from the perspectives of minimizing cost and risk, as well as for improving the diversification level.

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  • 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.
    • Handle: RePEc:eee:appene:v:229:y:2018:i:c:p:522-536
    DOI: 10.1016/j.apenergy.2018.08.028
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    1. Chen, Hao & Tang, Bao-Jun & Liao, Hua & Wei, Yi-Ming, 2016. "A multi-period power generation planning model incorporating the non-carbon external costs: A case study of China," Applied Energy, Elsevier, vol. 183(C), pages 1333-1345.
    2. Taner, Tolga & Sivrioglu, Mecit, 2015. "Energy–exergy analysis and optimisation of a model sugar factory in Turkey," Energy, Elsevier, vol. 93(P1), pages 641-654.
    3. Marrero, Gustavo A. & Ramos-Real, Francisco Javier, 2010. "Electricity generation cost in isolated system: The complementarities of natural gas and renewables in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2808-2818, December.
    4. de-Llano Paz, Fernando & Antelo, Susana Iglesias & Calvo Silvosa, Anxo & Soares, Isabel, 2014. "The technological and environmental efficiency of the EU-27 power mix: An evaluation based on MPT," Energy, Elsevier, vol. 69(C), pages 67-81.
    5. Awerbuch, Shimon & Yang, Spencer, 2007. "Efficient electricity generating portfolios for Europe: maximising energy security and climate change mitigation," EIB Papers 7/2007, European Investment Bank, Economics Department.
    6. Losekann, Luciano & Marrero, Gustavo A. & Ramos-Real, Francisco J. & de Almeida, Edmar Luiz Fagundes, 2013. "Efficient power generating portfolio in Brazil: Conciliating cost, emissions and risk," Energy Policy, Elsevier, vol. 62(C), pages 301-314.
    7. Hui, Jingxuan & Cai, Wenjia & Wang, Can & Ye, Minhua, 2017. "Analyzing the penetration barriers of clean generation technologies in China’s power sector using a multi-region optimization model," Applied Energy, Elsevier, vol. 185(P2), pages 1809-1820.
    8. Roques, Fabien A. & Newbery, David M. & Nuttall, William J., 2008. "Fuel mix diversification incentives in liberalized electricity markets: A Mean-Variance Portfolio theory approach," Energy Economics, Elsevier, vol. 30(4), pages 1831-1849, July.
    9. Cai, Yiyong & Arora, Vipin, 2015. "Disaggregating electricity generation technologies in CGE models: A revised technology bundle approach with an application to the U.S. Clean Power Plan," Applied Energy, Elsevier, vol. 154(C), pages 543-555.
    10. Chuang, Ming Chih & Ma, Hwong Wen, 2013. "Energy security and improvements in the function of diversity indices—Taiwan energy supply structure case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 9-20.
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Ahn, Joongha & Woo, JongRoul & Lee, Jongsu, 2015. "Optimal allocation of energy sources for sustainable development in South Korea: Focus on the electric power generation industry," Energy Policy, Elsevier, vol. 78(C), pages 78-90.
    13. Marrero, Gustavo A. & Puch, Luis A. & Ramos-Real, Francisco J., 2015. "Mean-variance portfolio methods for energy policy risk management," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 246-264.
    14. 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.
    15. Costa, Oswaldo L.V. & de Oliveira Ribeiro, Celma & Rego, Erik Eduardo & Stern, Julio Michael & Parente, Virginia & Kileber, Solange, 2017. "Robust portfolio optimization for electricity planning: An application based on the Brazilian electricity mix," Energy Economics, Elsevier, vol. 64(C), pages 158-169.
    16. Bar-Lev, Dan & Katz, Steven, 1976. "A Portfolio Approach to Fossil Fuel Procurement in the Electric Utility Industry," Journal of Finance, American Finance Association, vol. 31(3), pages 933-947, June.
    17. Zhang, Dongjie & Ma, Linwei & Liu, Pei & Zhang, Lili & Li, Zheng, 2012. "A multi-period superstructure optimisation model for the optimal planning of China's power sector considering carbon dioxide mitigation," Energy Policy, Elsevier, vol. 41(C), pages 173-183.
    18. 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.
    19. Stempien, J.P. & Chan, S.H., 2017. "Addressing energy trilemma via the modified Markowitz Mean-Variance Portfolio Optimization theory," Applied Energy, Elsevier, vol. 202(C), pages 228-237.
    20. deLlano-Paz, Fernando & Martínez Fernandez, Paulino & Soares, Isabel, 2016. "Addressing 2030 EU policy framework for energy and climate: Cost, risk and energy security issues," Energy, Elsevier, vol. 115(P2), pages 1347-1360.
    21. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.
    22. Taner, Tolga & Sivrioglu, Mecit, 2017. "A techno-economic & cost analysis of a turbine power plant: A case study for sugar plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 722-730.
    23. Cai, Wenjia & Wang, Can & Wang, Ke & Zhang, Ying & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's electricity sector," Energy Policy, Elsevier, vol. 35(12), pages 6445-6456, December.
    24. Delarue, Erik & De Jonghe, Cedric & Belmans, Ronnie & D'haeseleer, William, 2011. "Applying portfolio theory to the electricity sector: Energy versus power," Energy Economics, Elsevier, vol. 33(1), pages 12-23, January.
    25. Arnesano, M. & Carlucci, A.P. & Laforgia, D., 2012. "Extension of portfolio theory application to energy planning problem – The Italian case," Energy, Elsevier, vol. 39(1), pages 112-124.
    26. Zhu, Lei & Fan, Ying, 2010. "Optimization of China's generating portfolio and policy implications based on portfolio theory," Energy, Elsevier, vol. 35(3), pages 1391-1402.
    27. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.
    28. Lucheroni, Carlo & Mari, Carlo, 2017. "CO2 volatility impact on energy portfolio choice: A fully stochastic LCOE theory analysis," Applied Energy, Elsevier, vol. 190(C), pages 278-290.
    29. Wu, Jung-Hua & Huang, Yun-Hsun, 2014. "Electricity portfolio planning model incorporating renewable energy characteristics," Applied Energy, Elsevier, vol. 119(C), pages 278-287.
    30. Hickey, Emily A. & Lon Carlson, J. & Loomis, David, 2010. "Issues in the determination of the optimal portfolio of electricity supply options," Energy Policy, Elsevier, vol. 38(5), pages 2198-2207, May.
    31. deLlano-Paz, Fernando & Calvo-Silvosa, Anxo & Iglesias Antelo, Susana & Soares, Isabel, 2015. "The European low-carbon mix for 2030: The role of renewable energy sources in an environmentally and socially efficient approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 49-61.
    32. Wang, Ke & Wang, Can & Lu, Xuedu & Chen, Jining, 2007. "Scenario analysis on CO2 emissions reduction potential in China's iron and steel industry," Energy Policy, Elsevier, vol. 35(4), pages 2320-2335, April.
    33. Cheng, Rui & Xu, Zhaofeng & Liu, Pei & Wang, Zhe & Li, Zheng & Jones, Ian, 2015. "A multi-region optimization planning model for China’s power sector," Applied Energy, Elsevier, vol. 137(C), pages 413-426.
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    7. Cassidy K. Buhler & Hande Y. Benson, 2023. "Efficient Solution of Portfolio Optimization Problems via Dimension Reduction and Sparsification," Papers 2306.12639, arXiv.org.
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