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A decision-making tool for project investments based on real options: the case of wind power generation

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  • J. Muñoz
  • J. Contreras
  • J. Caamaño
  • P. Correia

Abstract

This paper presents how to apply a decision-making tool based on real options to assess the investment in a wind energy plant. The work shows six case studies where the main model’s parameters are analyzed. The uncertainty coming from wind regimes is simulated by using Weibull distributions and the volatility of market prices is obtained from the mean reverting process of the Ornstein-Uhlenbeck type, also known as Geometric Mean Reversion (GMR). From these and other values, such as investment and maintenance costs, the Net Present Value (NPV) curve, made up of different values of NPV in different periods of the investment is calculated, as well as its average volatility. Having the key parameters of the model, a real options valuation method is applied. The volatility, strength of reversion and long-term trend of the NPV curve reflecting different periods are inserted into a trinomial investment option valuation tree. From this, it is possible to calculate the probabilities of investing right now (exercise), deferring the investment (wait), or not investing at all (abandon). This powerful decision-making tool allows wind energy investors to decide whether to invest in many different scenarios. Copyright Springer Science+Business Media, LLC 2011

Suggested Citation

  • J. Muñoz & J. Contreras & J. Caamaño & P. Correia, 2011. "A decision-making tool for project investments based on real options: the case of wind power generation," Annals of Operations Research, Springer, vol. 186(1), pages 465-490, June.
    • Handle: RePEc:spr:annopr:v:186:y:2011:i:1:p:465-490:10.1007/s10479-011-0856-9
    DOI: 10.1007/s10479-011-0856-9
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    5. Christina E. Bannier, 2016. "Bewertungsmethoden in der Projektfinanzierung Erneuerbarer Energien [Valuation Methods for Renewable Energy Projects]," Schmalenbach Journal of Business Research, Springer, vol. 68(1), pages 75-110, April.
    6. Chun-Hung Chiu & Shui-Hung Hou & Xun Li & Wei Liu, 2017. "Real options approach for fashionable and perishable products using stock loan with regime switching," Annals of Operations Research, Springer, vol. 257(1), pages 357-377, October.
    7. Yanzhao Li & Ju'e Guo & Yongwu Li & Xu Zhang, 2021. "Optimal exit decision of venture capital under time-inconsistent preferences," Papers 2103.11557, arXiv.org.
    8. Haifeng Zhang & Feng Gao & Jiang Wu & Kun Liu & Xiaolin Liu, 2012. "Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market," Energies, MDPI, vol. 5(11), pages 1-20, November.
    9. Cheng, Cheng & Dong, Kangyin & Wang, Zhen & Liu, Shulin & Jurasz, Jakub & Zhang, Haoran, 2023. "Rethinking the evaluation of solar photovoltaic projects under YieldCo mode: A real option perspective," Applied Energy, Elsevier, vol. 336(C).
    10. Gorupec Natalia & Brehmer Nataliia & Tiberius Victor & Kraus Sascha, 2022. "Tackling uncertain future scenarios with real options: A review and research framework," The Irish Journal of Management, Sciendo, vol. 41(1), pages 69-88, July.
    11. Kim, Kyoung-Kuk & Lee, Chi-Guhn, 2012. "Evaluation and optimization of feed-in tariffs," Energy Policy, Elsevier, vol. 49(C), pages 192-203.
    12. Delaney, L., 2016. "Equilibrium Investment in High Frequency Trading Technology: A Real Options Approach," Working Papers 15/14, Department of Economics, City University London.
    13. Andreas Welling, 2017. "Green Finance: Recent developments, characteristics and important actors," FEMM Working Papers 170002, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    14. Chi Truong & Matteo Malavasi & Han Li & Stefan Trueck & Pavel V. Shevchenko, 2024. "Optimal dynamic climate adaptation pathways: a case study of New York City," Papers 2402.02745, arXiv.org.
    15. Carol Alexander & Xi Chen, 2021. "Model risk in real option valuation," Annals of Operations Research, Springer, vol. 299(1), pages 1025-1056, April.
    16. Aleksandr Babkin & Nadezhda Kvasha & Daniil Demidenko & Ekaterina Malevskaia-Malevich & Evgeny Voroshin, 2022. "Methodology for Economic Analysis of Highly Uncertain Innovative Projects of Improbability Type," Risks, MDPI, vol. 11(1), pages 1-20, December.
    17. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    18. Nadarajah, Selvaprabu & Secomandi, Nicola, 2023. "A review of the operations literature on real options in energy," European Journal of Operational Research, Elsevier, vol. 309(2), pages 469-487.
    19. Locatelli, Giorgio & Invernizzi, Diletta Colette & Mancini, Mauro, 2016. "Investment and risk appraisal in energy storage systems: A real options approach," Energy, Elsevier, vol. 104(C), pages 114-131.
    20. Delaney, Laura, 2018. "Investment in high-frequency trading technology: A real options approach," European Journal of Operational Research, Elsevier, vol. 270(1), pages 375-385.
    21. Kozlova, Mariia, 2017. "Real option valuation in renewable energy literature: Research focus, trends and design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 180-196.
    22. Zhou, Shan & Yang, Pu, 2020. "Risk management in distributed wind energy implementing Analytic Hierarchy Process," Renewable Energy, Elsevier, vol. 150(C), pages 616-623.
    23. Huberts, Nick F.D. & Thijssen, Jacco J.J., 2023. "Optimal timing of non-pharmaceutical interventions during an epidemic," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1366-1389.
    24. Contreras, Javier & Rodríguez, Yeny E., 2014. "GARCH-based put option valuation to maximize benefit of wind investors," Applied Energy, Elsevier, vol. 136(C), pages 259-268.

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