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Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty

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  • Bruno, Sergio
  • Ahmed, Shabbir
  • Shapiro, Alexander
  • Street, Alexandre

Abstract

Strategies for investing in renewable energy projects present high risks associated with generation and price volatility and dynamics. Existing approaches for determining optimal strategies are based on real options theory, that often simplify the uncertainty process, or on stochastic programming approaches, that simplify the dynamic aspects. In this paper, we bridge the gap between these approaches by developing a multistage stochastic programming approach that includes real options such as postponing, hedging with fixed (forward) contracts and combination with other sources. The proposed model is solved by a procedure based on the Stochastic Dual Dynamic Programming (SDDP) method. The framework is extended to the risk averse setting. A specific case study in investment in hydro and wind projects in the Brazilian market is used to illustrate that the investment strategies generated by the proposed approach are efficient.

Suggested Citation

  • Bruno, Sergio & Ahmed, Shabbir & Shapiro, Alexander & Street, Alexandre, 2016. "Risk neutral and risk averse approaches to multistage renewable investment planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 250(3), pages 979-989.
    • Handle: RePEc:eee:ejores:v:250:y:2016:i:3:p:979-989
    DOI: 10.1016/j.ejor.2015.10.013
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    References listed on IDEAS

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    8. Arega Getaneh Abate & Rossana Riccardi & Carlos Ruiz, 2022. "Contract design in electricity markets with high penetration of renewables: A two-stage approach," Papers 2201.09927, arXiv.org, revised Jun 2022.
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    12. Skolfield, J. Kyle & Escobedo, Adolfo R., 2022. "Operations research in optimal power flow: A guide to recent and emerging methodologies and applications," European Journal of Operational Research, Elsevier, vol. 300(2), pages 387-404.
    13. Ritzenhofen, Ingmar & Birge, John R. & Spinler, Stefan, 2016. "The structural impact of renewable portfolio standards and feed-in tariffs on electricity markets," European Journal of Operational Research, Elsevier, vol. 255(1), pages 224-242.
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    15. Davi Valladão & Thuener Silva & Marcus Poggi, 2019. "Time-consistent risk-constrained dynamic portfolio optimization with transactional costs and time-dependent returns," Annals of Operations Research, Springer, vol. 282(1), pages 379-405, November.
    16. Shubin Wang & Weijie Li & Hasan Dincer & Serhat Yuksel, 2019. "Recognitive Approach to the Energy Policies and Investments in Renewable Energy Resources via the Fuzzy Hybrid Models," Energies, MDPI, vol. 12(23), pages 1-17, November.
    17. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    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. Jonas Hinker & Thomas Wohlfahrt & Emily Drewing & Sergio Felipe Contreras Paredes & Daniel Mayorga González & Johanna M. A. Myrzik, 2018. "Adaptable Energy Systems Integration by Modular, Standardized and Scalable System Architectures: Necessities and Prospects of Any Time Transition," Energies, MDPI, vol. 11(3), pages 1-17, March.
    20. Pineda, Salvador & Boomsma, Trine K. & Wogrin, Sonja, 2018. "Renewable generation expansion under different support schemes: A stochastic equilibrium approach," European Journal of Operational Research, Elsevier, vol. 266(3), pages 1086-1099.

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