IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v40y2014icp224-236.html
   My bibliography  Save this article

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

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032114006418
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2014.07.189?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. Silvio Contessi & Li Li & Katheryn N. Russ, 2013. "Bank vs. bond financing over the business cycle," Economic Synopses, Federal Reserve Bank of St. Louis.
    5. 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.
    6. Han, Yinghua & Mays, Ian, 1996. "Feasibility study of wind energy potential in China," Renewable Energy, Elsevier, vol. 9(1), pages 810-814.
    7. 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).
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Giang Ho & Miss Yinqiu Lu, 2013. "A Financial Conditions Index for Poland," IMF Working Papers 2013/252, International Monetary Fund.
    16. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xu Lei & Tang Shiyun & Deng Yanfei & Yuan Yuan, 2020. "Sustainable operation-oriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China," Annals of Operations Research, Springer, vol. 290(1), pages 223-241, July.
    2. Tu, Qiang & Betz, Regina & Mo, Jianlei & Fan, Ying & Liu, Yu, 2019. "Achieving grid parity of wind power in China – Present levelized cost of electricity and future evolution," Applied Energy, Elsevier, vol. 250(C), pages 1053-1064.
    3. Watts, David & Oses, Nicolás & Pérez, Rodrigo, 2016. "Assessment of wind energy potential in Chile: A project-based regional wind supply function approach," Renewable Energy, Elsevier, vol. 96(PA), pages 738-755.
    4. T. Chatzivasileiadis & F. Estrada & M. W. Hofkes & R. S. J. Tol, 2019. "Systematic Sensitivity Analysis of the Full Economic Impacts of Sea Level Rise," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1183-1217, March.
    5. Shahryari, E. & Shayeghi, H. & Mohammadi-ivatloo, B. & Moradzadeh, M., 2019. "A copula-based method to consider uncertainties for multi-objective energy management of microgrid in presence of demand response," Energy, Elsevier, vol. 175(C), pages 879-890.
    6. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    7. Fan, Xiao-chao & Wang, Wei-qing, 2016. "Spatial patterns and influencing factors of China׳s wind turbine manufacturing industry: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 482-496.
    8. Watts, David & Durán, Pablo & Flores, Yarela, 2017. "How does El Niño Southern Oscillation impact the wind resource in Chile? A techno-economical assessment of the influence of El Niño and La Niña on the wind power," Renewable Energy, Elsevier, vol. 103(C), pages 128-142.
    9. Zhang, Dayong & Cao, Hong & Zou, Peijiang, 2016. "Exuberance in China's renewable energy investment: Rationality, capital structure and implications with firm level evidence," Energy Policy, Elsevier, vol. 95(C), pages 468-478.
    10. Enevoldsen, Peter, 2016. "Onshore wind energy in Northern European forests: Reviewing the risks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1251-1262.
    11. Pejman Bahramian, 2021. "Integration of wind power into an electricity system using pumped-storage: Economic challenges and stakeholder impacts," Working Paper 1478, Economics Department, Queen's University.
    12. Pejman Bahramian & Glenn P. Jenkins & Frank Milne, 2023. "Integration Of Wind Power into An Electricity System Using Pumped Storage: Economic Challenges and Stakeholder Impacts," Development Discussion Papers 2023-07, JDI Executive Programs.
    13. Brown, Alistair, 2016. "The need for improved financial reporting of a developing country energy utility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1448-1454.
    14. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.
    15. Ioannou, Anastasia & Angus, Andrew & Brennan, Feargal, 2017. "Risk-based methods for sustainable energy system planning: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 602-615.
    16. Liu, Chunyu & Zheng, Xinrui & Yang, Haibin & Tang, Waiching & Sang, Guochen & Cui, Hongzhi, 2023. "Techno-economic evaluation of energy storage systems for concentrated solar power plants using the Monte Carlo method," Applied Energy, Elsevier, vol. 352(C).
    17. Stetter, Chris & Piel, Jan-Hendrik & Hamann, Julian F.H. & Breitner, Michael H., 2020. "Competitive and risk-adequate auction bids for onshore wind projects in Germany," Energy Economics, Elsevier, vol. 90(C).
    18. Niu, Shuwen & Liu, Yiyue & Ding, Yongxia & Qu, Wei, 2016. "China׳s energy systems transformation and emissions peak," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 782-795.
    19. Zheng, Donglin & Yu, Lijun & Wang, Lizhen, 2019. "A techno-economic-risk decision-making methodology for large-scale building energy efficiency retrofit using Monte Carlo simulation," Energy, Elsevier, vol. 189(C).
    20. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    21. Cunico, Maria Laura & Flores, Julio Rolando & Vecchietti, Aldo, 2017. "Investment in the energy sector: An optimization model that contemplates several uncertain parameters," Energy, Elsevier, vol. 138(C), pages 831-845.
    22. Chen, Huadong & Wang, Can & Cai, Wenjia & Wang, Jianhui, 2018. "Simulating the impact of investment preference on low-carbon transition in power sector," Applied Energy, Elsevier, vol. 217(C), pages 440-455.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Farrell, Niall & Donoghue, Cathal O’ & Morrissey, Karyn, 2015. "Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: An Irish case study," Energy Policy, Elsevier, vol. 78(C), pages 62-77.
    2. Jin, Xin & Zhang, Zhaolong & Shi, Xiaoqiang & Ju, Wenbin, 2014. "A review on wind power industry and corresponding insurance market in China: Current status and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 1069-1082.
    3. Li, Cun-bin & Li, Peng & Feng, Xia, 2014. "Analysis of wind power generation operation management risk in China," Renewable Energy, Elsevier, vol. 64(C), pages 266-275.
    4. Huiru Zhao & Sen Guo & Hongze Li, 2015. "Economic Impact Assessment of Wind Power Integration: A Quasi-Public Goods Property Perspective," Energies, MDPI, vol. 8(8), pages 1-26, August.
    5. Xu Lei & Tang Shiyun & Deng Yanfei & Yuan Yuan, 2020. "Sustainable operation-oriented investment risk evaluation and optimization for renewable energy project: a case study of wind power in China," Annals of Operations Research, Springer, vol. 290(1), pages 223-241, July.
    6. Lam, J.C.K. & Woo, C.K. & Kahrl, F. & Yu, W.K., 2013. "What moves wind energy development in China? Show me the money!," Applied Energy, Elsevier, vol. 105(C), pages 423-429.
    7. Li, Aitong & Sun, Ying & Song, Xiaobin, 2023. "Gradual improvement and reactive intervention: China's policy pathway for developing the wind power industry," Renewable Energy, Elsevier, vol. 216(C).
    8. Jaroslava Janekova & Jana Fabianova & Andrea Rosova, 2016. "Environmental And Economic Aspects In Decision Making Of The Investment Project “Wind Park”," Polish Journal of Management Studies, Czestochowa Technical University, Department of Management, vol. 13(1), pages 90-100, June.
    9. Fan, Xiao-chao & Wang, Wei-qing, 2016. "Spatial patterns and influencing factors of China׳s wind turbine manufacturing industry: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 482-496.
    10. Gosens, Jorrit & Lu, Yonglong, 2014. "Prospects for global market expansion of China’s wind turbine manufacturing industry," Energy Policy, Elsevier, vol. 67(C), pages 301-318.
    11. Yuan, Jiahai & Sun, Shenghui & Shen, Jiakun & Xu, Yan & Zhao, Changhong, 2014. "Wind power supply chain in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 356-369.
    12. Ming, Zeng & Song, Xue & Mingjuan, Ma & Xiaoli, Zhu, 2013. "New energy bases and sustainable development in China: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 169-185.
    13. Cui, Yu & Khan, Sufyan Ullah & Li, Zhixue & Zhao, Minjuan, 2021. "Environmental effect, price subsidy and financial performance: Evidence from Chinese new energy enterprises," Energy Policy, Elsevier, vol. 149(C).
    14. Cui, Qi & He, Ling & Han, Guoyi & Chen, Hao & Cao, Juanjuan, 2020. "Review on climate and water resource implications of reducing renewable power curtailment in China: A nexus perspective," Applied Energy, Elsevier, vol. 267(C).
    15. Hakan Kara & Pinar Ozlu & Deren Unalmis, 2015. "Turkiye icin Finansal Kosullar Endeksi," Central Bank Review, Research and Monetary Policy Department, Central Bank of the Republic of Turkey, vol. 15(3), pages 41-73.
    16. Xin-Rui Liu & Si-Luo Sun & Qiu-Ye Sun & Wei-Yang Zhong, 2020. "Time-Scale Economic Dispatch of Electricity-Heat Integrated System Based on Users’ Thermal Comfort," Energies, MDPI, vol. 13(20), pages 1-27, October.
    17. Haghi, Ehsan & Raahemifar, Kaamran & Fowler, Michael, 2018. "Investigating the effect of renewable energy incentives and hydrogen storage on advantages of stakeholders in a microgrid," Energy Policy, Elsevier, vol. 113(C), pages 206-222.
    18. Yiqi Chu & Chengcai Li & Yefang Wang & Jing Li & Jian Li, 2016. "A Long-Term Wind Speed Ensemble Forecasting System with Weather Adapted Correction," Energies, MDPI, vol. 9(11), pages 1-20, October.
    19. Valentine, Scott Victor, 2014. "The socio-political economy of electricity generation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 416-429.
    20. Liao, Zhongju, 2016. "The evolution of wind energy policies in China (1995–2014): An analysis based on policy instruments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 464-472.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:40:y:2014:i:c:p:224-236. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.