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Real Options Valuation of Wind Energy Based on the Empirical Production Uncertainty

Author

Listed:
  • Didier Nibbering
  • Coos van Buuren
  • Wei Wei

Abstract

Using a real options approach, we analyze the valuation of wind energy projects and associated investment decisions while accounting for both price and production uncertainty. We propose a new approach to explicitly incorporate production uncertainty into the valuation. Specifically, we account for the production risk using a stochastic process for wind speed, a cubic spline model for the conversion of wind speed to wind electricity, and a Bayesian procedure for estimating and forecasting the wind electricity processes. In a case-study on a comprehensive dataset of a Dutch offshore wind farm, we evaluate the financial consequences of ignoring production risk for different levelized costs of energy values. We find that fixing the production at a capacity factor value leads to substantial underestimation of the real options value, and relying on theoretical instead of empirical power curves leads to overestimation.

Suggested Citation

  • Didier Nibbering & Coos van Buuren & Wei Wei, 2021. "Real Options Valuation of Wind Energy Based on the Empirical Production Uncertainty," Monash Econometrics and Business Statistics Working Papers 19/21, Monash University, Department of Econometrics and Business Statistics.
  • Handle: RePEc:msh:ebswps:2021-19
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    File URL: https://www.monash.edu/business/ebs/research/publications/ebs/wp19-2021.pdf
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    References listed on IDEAS

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    1. Kroniger, Daniel & Madlener, Reinhard, 2014. "Hydrogen storage for wind parks: A real options evaluation for an optimal investment in more flexibility," Applied Energy, Elsevier, vol. 136(C), pages 931-946.
    2. Luis M. Abadie & José M. Chamorro, 2014. "Valuation of Wind Energy Projects: A Real Options Approach," Energies, MDPI, vol. 7(5), pages 1-38, May.
    3. Matthäus, David & Schwenen, Sebastian & Wozabal, David, 2021. "Renewable auctions: Bidding for real options," European Journal of Operational Research, Elsevier, vol. 291(3), pages 1091-1105.
    4. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    5. Franses, Philip Hans & Haldrup, Niels, 1994. "The Effects of Additive Outliers on Tests for Unit Roots and Cointegration," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 471-478, October.
    6. Ergemen, Yunus Emre & Haldrup, Niels & Rodríguez-Caballero, Carlos Vladimir, 2016. "Common long-range dependence in a panel of hourly Nord Pool electricity prices and loads," Energy Economics, Elsevier, vol. 60(C), pages 79-96.
    7. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    8. Möst, Dominik & Keles, Dogan, 2010. "A survey of stochastic modelling approaches for liberalised electricity markets," European Journal of Operational Research, Elsevier, vol. 207(2), pages 543-556, December.
    9. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    10. Monjas-Barroso, Manuel & Balibrea-Iniesta, José, 2013. "Valuation of projects for power generation with renewable energy: A comparative study based on real regulatory options," Energy Policy, Elsevier, vol. 55(C), pages 335-352.
    11. Chib, Siddhartha & Greenberg, Edward, 2010. "Additive cubic spline regression with Dirichlet process mixture errors," Journal of Econometrics, Elsevier, vol. 156(2), pages 322-336, June.
    12. Lion Hirth, Falko Ueckerdt, and Ottmar Edenhofer, 2016. "Why Wind Is Not Coal: On the Economics of Electricity Generation," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    13. Finjord, Fredrik & Hagspiel, Verena & Lavrutich, Maria & Tangen, Marius, 2018. "The impact of Norwegian-Swedish green certificate scheme on investment behavior: A wind energy case study," Energy Policy, Elsevier, vol. 123(C), pages 373-389.
    14. Díaz, Guzmán & Moreno, Blanca & Coto, José & Gómez-Aleixandre, Javier, 2015. "Valuation of wind power distributed generation by using Longstaff–Schwartz option pricing method," Applied Energy, Elsevier, vol. 145(C), pages 223-233.
    15. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    16. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    17. Venetsanos, Konstantinos & Angelopoulou, Penelope & Tsoutsos, Theocharis, 2002. "Renewable energy sources project appraisal under uncertainty: the case of wind energy exploitation within a changing energy market environment," Energy Policy, Elsevier, vol. 30(4), pages 293-307, March.
    18. Perron, Pierre & Qu, Zhongjun, 2007. "A simple modification to improve the finite sample properties of Ng and Perron's unit root tests," Economics Letters, Elsevier, vol. 94(1), pages 12-19, January.
    19. Ernstsen, Rune Ramsdal & Boomsma, Trine Krogh, 2018. "Valuation of power plants," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1153-1174.
    20. J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
    21. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    22. Branker, K. & Pathak, M.J.M. & Pearce, J.M., 2011. "A review of solar photovoltaic levelized cost of electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4470-4482.
    23. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    24. 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.
    25. Boomsma, Trine Krogh & Meade, Nigel & Fleten, Stein-Erik, 2012. "Renewable energy investments under different support schemes: A real options approach," European Journal of Operational Research, Elsevier, vol. 220(1), pages 225-237.
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    More about this item

    Keywords

    OR in energy; wind electricity; production uncertainty; real options; hierarchical Bayesian model;
    All these keywords.

    JEL classification:

    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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