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Profitability of wind energy investments in China using a Monte Carlo approach for the treatment of uncertainties

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  • Caralis, George
  • Diakoulaki, Danae
  • Yang, Peijin
  • Gao, Zhiqiu
  • Zervos, Arthouros
  • Rados, Kostas

Abstract

China is the global leader in terms of installed wind capacity. Further, wind energy development is expected for the next years and decades to meet the continuously increasing electricity demand and the need of using clean domestic energy. Since 2009 China is divided into four geographical regions, each assigned with a different benchmark on-grid tariff. Moreover the existing infrastructures are not equally developed throughout the country, making investment decisions more complicated and risky. The scope of this paper is to apply an innovative methodology and evaluate the attractiveness of each region for wind energy development, by taking into consideration all relevant investment risks, such as wind potential, wind curtailment, access to the grid and macroeconomic parameters. To this purpose a Monte Carlo simulation approach, integrated into a typical financial model, is implemented in each of the four regions, performing many hundreds of iterations, each characterized by a randomly selected set of the examined uncertain parameters. This approach intends to provide information to private investors doing a first exploratory research in the huge country׳s area in order to decide whether and where to invest, as well as to policy makers to help them assess critical policy parameters and investigate different scenarios of wind energy development. The evaluation of the current framework for wind energy development in China verifies that the existing system of feed-in tariffs in China is very effective for the balanced deployment of wind energy in the whole country. However, it is shown that the risk of curtailment and grid accessibility may significantly reduce the potential profitability of wind energy investments in all four regions. Priority for development of infrastructures should be given in isolated northern windy areas with high-accumulation of wind farms.

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  • Caralis, George & Diakoulaki, Danae & Yang, Peijin & Gao, Zhiqiu & Zervos, Arthouros & Rados, Kostas, 2014. "Profitability of wind energy investments in China using a Monte Carlo approach for the treatment of uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 224-236.
    • Handle: RePEc:eee:rensus:v:40:y:2014:i:c:p:224-236
    DOI: 10.1016/j.rser.2014.07.189
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    1. Gass, V. & Strauss, F. & Schmidt, J. & Schmid, E., 2011. "Assessing the effect of wind power uncertainty on profitability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2677-2683, August.
    2. Ming, Zeng & Kun, Zhang & Jun, Dong, 2013. "Overall review of China's wind power industry: Status quo, existing problems and perspective for future development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 379-386.
    3. Han, Yinghua & Mays, Ian, 1996. "Feasibility study of wind energy potential in China," Renewable Energy, Elsevier, vol. 9(1), pages 810-814.
    4. Montes, German Martinez & Martin, Enrique Prados & Bayo, Javier Alegre & Garcia, Javier Ordoñez, 2011. "The applicability of computer simulation using Monte Carlo techniques in windfarm profitability analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4746-4755.
    5. Falconett, Irina & Nagasaka, Ken, 2010. "Comparative analysis of support mechanisms for renewable energy technologies using probability distributions," Renewable Energy, Elsevier, vol. 35(6), pages 1135-1144.
    6. Dong He, 2013. "Hong Kong’s Approach to Financial Stability," International Journal of Central Banking, International Journal of Central Banking, vol. 9(1), pages 299-313, March.
    7. Yang, Mian & Patiño-Echeverri, Dalia & Yang, Fuxia, 2012. "Wind power generation in China: Understanding the mismatch between capacity and generation," Renewable Energy, Elsevier, vol. 41(C), pages 145-151.
    8. di Mauro, Filippo & Caristi, Pierluigi & Couderc, Stéphane & di Maria, Angela & Ho, Lauren & Grewal, Beljeet Kaur & Masciantonio, Sergio & Ongena, Steven & Zaher, Sajjad, 2013. "Islamic finance in Europe," Occasional Paper Series 146, European Central Bank.
    9. Kumbaroğlu, Gürkan & Madlener, Reinhard, 2011. "Evaluation of Economically Optimal Retrofit Investment Options for Energy Savings in Buildings," FCN Working Papers 14/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    10. Yu, Dayang & Liang, Jun & Han, Xueshan & Zhao, Jianguo, 2011. "Profiling the regional wind power fluctuation in China," Energy Policy, Elsevier, vol. 39(1), pages 299-306, January.
    11. Yanbin Chen & Fangxing Li & Zhesheng Qiu, 2013. "Housing and Saving with Finance Imperfection," Annals of Economics and Finance, Society for AEF, vol. 14(1), pages 207-248, May.
    12. Giang Ho & Miss Yinqiu Lu, 2013. "A Financial Conditions Index for Poland," IMF Working Papers 2013/252, International Monetary Fund.
    13. Montes, Germán Martínez & Martín, Enrique Prados, 2007. "Profitability of wind energy: Short-term risk factors and possible improvements," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(9), pages 2191-2200, December.
    14. Zhao, Xiaoli & Wang, Feng & Wang, Mei, 2012. "Large-scale utilization of wind power in China: Obstacles of conflict between market and planning," Energy Policy, Elsevier, vol. 48(C), pages 222-232.
    15. Silvio Contessi & Li Li & Katheryn N. Russ, 2013. "Bank vs. bond financing over the business cycle," Economic Synopses, Federal Reserve Bank of St. Louis.
    16. Mavrotas, George & Florios, Kostas & Vlachou, Dimitra, 2010. "Energy planning of a hospital using Mathematical Programming and Monte Carlo simulation for dealing with uncertainty in the economic parameters," MPRA Paper 105754, University Library of Munich, Germany.
    Full references (including those not matched with items on IDEAS)

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