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Low or No subsidy? Proposing a regional power grid based wind power feed-in tariff benchmark price mechanism in China

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  • Zhang, Ruixiaoxiao
  • Shimada, Koji
  • Ni, Meng
  • Shen, Geoffrey Q.P.
  • Wong, Johnny K.W.

Abstract

The Chinese government plans to adopt a low or no subsidy policy mechanism on renewable energy power development in the future. To achieve a balance between reducing financial burden on the government and ensuring profitability of investors as well as to account for the regional differences in China, a novel regional wind power grid feed-in tariff benchmark price mechanism by Net Present Value (NPV) method and Real Option (RO) method is proposed in this paper. The results voice support on the appropriateness of gradually decreasing the wind feed-in tariff (FIT) benchmark price to as low as the coal-fired FIT. The proposed FIT price level is presented as a price range on the basis of a guaranteed Internal Rate of Return (IRR) falls in between 8% to 15% for wind power investors. The results indicate that the current FIT price should be readjusted and redistributed. Although the FIT price in Central and South China grids is recommended to be relatively high, the NPV of wind farm project value in six regional grids are at the same level.

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  • Zhang, Ruixiaoxiao & Shimada, Koji & Ni, Meng & Shen, Geoffrey Q.P. & Wong, Johnny K.W., 2020. "Low or No subsidy? Proposing a regional power grid based wind power feed-in tariff benchmark price mechanism in China," Energy Policy, Elsevier, vol. 146(C).
  • Handle: RePEc:eee:enepol:v:146:y:2020:i:c:s030142152030481x
    DOI: 10.1016/j.enpol.2020.111758
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    as
    1. Esmaieli, M. & Ahmadian, M., 2018. "The effect of research and development incentive on wind power investment, a system dynamics approach," Renewable Energy, Elsevier, vol. 126(C), pages 765-773.
    2. Zhu, Lei & Fan, Ying, 2011. "A real options–based CCS investment evaluation model: Case study of China’s power generation sector," Applied Energy, Elsevier, vol. 88(12), pages 4320-4333.
    3. Davis, Graham A. & Owens, Brandon, 2003. "Optimizing the level of renewable electric R&D expenditures using real options analysis," Energy Policy, Elsevier, vol. 31(15), pages 1589-1608, December.
    4. Brauneis, Alexander & Mestel, Roland & Palan, Stefan, 2013. "Inducing low-carbon investment in the electric power industry through a price floor for emissions trading," Energy Policy, Elsevier, vol. 53(C), pages 190-204.
    5. Hu, Zheng & Wang, Jianhui & Byrne, John & Kurdgelashvili, Lado, 2013. "Review of wind power tariff policies in China," Energy Policy, Elsevier, vol. 53(C), pages 41-50.
    6. Fagiani, Riccardo & Barquín, Julián & Hakvoort, Rudi, 2013. "Risk-based assessment of the cost-efficiency and the effectivity of renewable energy support schemes: Certificate markets versus feed-in tariffs," Energy Policy, Elsevier, vol. 55(C), pages 648-661.
    7. Ritzenhofen, Ingmar & Spinler, Stefan, 2016. "Optimal design of feed-in-tariffs to stimulate renewable energy investments under regulatory uncertainty — A real options analysis," Energy Economics, Elsevier, vol. 53(C), pages 76-89.
    8. Zhao, Zhen-Yu & Chang, Rui-Dong & Chen, Yu-Long, 2016. "What hinder the further development of wind power in China?—A socio-technical barrier study," Energy Policy, Elsevier, vol. 88(C), pages 465-476.
    9. Zhang, M.M. & Zhou, D.Q. & Zhou, P. & Liu, G.Q., 2016. "Optimal feed-in tariff for solar photovoltaic power generation in China: A real options analysis," Energy Policy, Elsevier, vol. 97(C), pages 181-192.
    10. Fleten, S.-E. & Maribu, K.M. & Wangensteen, I., 2007. "Optimal investment strategies in decentralized renewable power generation under uncertainty," Energy, Elsevier, vol. 32(5), pages 803-815.
    11. Penizzotto, F. & Pringles, R. & Olsina, F., 2019. "Real options valuation of photovoltaic power investments in existing buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    12. Pringles, Rolando & Olsina, Fernando & Garcés, Francisco, 2015. "Real option valuation of power transmission investments by stochastic simulation," Energy Economics, Elsevier, vol. 47(C), pages 215-226.
    13. Bruck, Maira & Sandborn, Peter & Goudarzi, Navid, 2018. "A Levelized Cost of Energy (LCOE) model for wind farms that include Power Purchase Agreements (PPAs)," Renewable Energy, Elsevier, vol. 122(C), pages 131-139.
    14. Bøckman, Thor & Fleten, Stein-Erik & Juliussen, Erik & Langhammer, Håvard J. & Revdal, Ingemar, 2008. "Investment timing and optimal capacity choice for small hydropower projects," European Journal of Operational Research, Elsevier, vol. 190(1), pages 255-267, October.
    15. Zhao, Zhen-Yu & Chen, Yu-Long & Chang, Rui-Dong, 2016. "How to stimulate renewable energy power generation effectively? – China's incentive approaches and lessons," Renewable Energy, Elsevier, vol. 92(C), pages 147-156.
    16. Gollier, Christian & Proult, David & Thais, Francoise & Walgenwitz, Gilles, 2005. "Choice of nuclear power investments under price uncertainty: Valuing modularity," Energy Economics, Elsevier, vol. 27(4), pages 667-685, July.
    17. Wei, Yi-Ming & Chen, Hao & Chyong, Chi Kong & Kang, Jia-Ning & Liao, Hua & Tang, Bao-Jun, 2018. "Economic dispatch savings in the coal-fired power sector: An empirical study of China," Energy Economics, Elsevier, vol. 74(C), pages 330-342.
    18. Rigter, Jasper & Vidican, Georgeta, 2010. "Cost and optimal feed-in tariff for small scale photovoltaic systems in China," Energy Policy, Elsevier, vol. 38(11), pages 6989-7000, November.
    19. Shen, Jianfei & Luo, Chen, 2015. "Overall review of renewable energy subsidy policies in China – Contradictions of intentions and effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 1478-1488.
    20. Barbosa, Luciana & Ferrão, Paulo & Rodrigues, Artur & Sardinha, Alberto, 2018. "Feed-in tariffs with minimum price guarantees and regulatory uncertainty," Energy Economics, Elsevier, vol. 72(C), pages 517-541.
    21. Antweiler, Werner, 2017. "A two-part feed-in-tariff for intermittent electricity generation," Energy Economics, Elsevier, vol. 65(C), pages 458-470.
    22. Black, Fischer & Scholes, Myron S, 1972. "The Valuation of Option Contracts and a Test of Market Efficiency," Journal of Finance, American Finance Association, vol. 27(2), pages 399-417, May.
    23. Kim, Kyung-Taek & Lee, Deok-Joo & Park, Sung-Joon, 2014. "Evaluation of R&D investments in wind power in Korea using real option," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 335-347.
    24. Li, Cun-bin & Lu, Gong-shu & Wu, Si, 2013. "The investment risk analysis of wind power project in China," Renewable Energy, Elsevier, vol. 50(C), pages 481-487.
    25. Schmidt, J. & Lehecka, G. & Gass, V. & Schmid, E., 2013. "Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines," Energy Economics, Elsevier, vol. 40(C), pages 269-276.
    26. Kim, Kyoung-Kuk & Lee, Chi-Guhn, 2012. "Evaluation and optimization of feed-in tariffs," Energy Policy, Elsevier, vol. 49(C), pages 192-203.
    27. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    28. Wang, Xingwei & Cai, Yanpeng & Dai, Chao, 2014. "Evaluating China's biomass power production investment based on a policy benefit real options model," Energy, Elsevier, vol. 73(C), pages 751-761.
    29. Lin, Boqiang & Wesseh, Presley K., 2013. "Valuing Chinese feed-in tariffs program for solar power generation: A real options analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 474-482.
    30. Aho, Teemu & Virtanen, Iikka, 1983. "On relationships between ROI and IRR under inflation: A constant real cash-flow case," European Journal of Operational Research, Elsevier, vol. 13(3), pages 256-267, July.
    31. Fuss, Sabine & Johansson, Daniel J.A. & Szolgayova, Jana & Obersteiner, Michael, 2009. "Impact of climate policy uncertainty on the adoption of electricity generating technologies," Energy Policy, Elsevier, vol. 37(2), pages 733-743, February.
    32. Liu, Xiaoran & Ronn, Ehud I., 2020. "Using the binomial model for the valuation of real options in computing optimal subsidies for Chinese renewable energy investments," Energy Economics, Elsevier, vol. 87(C).
    33. Al–Zhour, Zeyad & Barfeie, Mahdiar & Soleymani, Fazlollah & Tohidi, Emran, 2019. "A computational method to price with transaction costs under the nonlinear Black–Scholes model," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 291-301.
    34. Nadarajah, Selvaprabu & Margot, François & Secomandi, Nicola, 2017. "Comparison of least squares Monte Carlo methods with applications to energy real options," European Journal of Operational Research, Elsevier, vol. 256(1), pages 196-204.
    35. Soberón, Alexandra & Stute, Winfried, 2017. "Assessing skewness, kurtosis and normality in linear mixed models," Journal of Multivariate Analysis, Elsevier, vol. 161(C), pages 123-140.
    36. Chowdhury, Reaz & Mahdy, M.R.C. & Alam, Tanisha Nourin & Al Quaderi, Golam Dastegir & Arifur Rahman, M., 2020. "Predicting the stock price of frontier markets using machine learning and modified Black–Scholes Option pricing model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
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