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


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


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

    1. Shapiro, Alexander & Tekaya, Wajdi & da Costa, Joari Paulo & Soares, Murilo Pereira, 2013. "Risk neutral and risk averse Stochastic Dual Dynamic Programming method," European Journal of Operational Research, Elsevier, vol. 224(2), pages 375-391.
    2. Gerd Infanger (ed.), 2011. "Stochastic Programming," International Series in Operations Research and Management Science, Springer, number 978-1-4419-1642-6, December.
    3. Alexandre Street, 2010. "On the Conditional Value-at-Risk probability-dependent utility function," Theory and Decision, Springer, vol. 68(1), pages 49-68, February.
    4. Shapiro, Alexander, 2011. "Analysis of stochastic dual dynamic programming method," European Journal of Operational Research, Elsevier, vol. 209(1), pages 63-72, February.
    5. 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.
    6. J. Bonnans & Zhihao Cen & Thibault Christel, 2012. "Energy contracts management by stochastic programming techniques," Annals of Operations Research, Springer, vol. 200(1), pages 199-222, November.
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    Cited by:

    1. Zheng, Wei & Li, Bo & Song, Dong-Ping, 2017. "Effects of risk-aversion on competing shipping lines’ pricing strategies with uncertain demands," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 337-356.
    2. Mahmutoğulları, Ali İrfan & Çavuş, Özlem & Aktürk, M. Selim, 2018. "Bounds on risk-averse mixed-integer multi-stage stochastic programming problems with mean-CVaR," European Journal of Operational Research, Elsevier, vol. 266(2), pages 595-608.
    3. 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.
    4. Talari, Saber & Shafie-khah, Miadreza & Osório, Gerardo J. & Aghaei, Jamshid & Catalão, João P.S., 2018. "Stochastic modelling of renewable energy sources from operators' point-of-view: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1953-1965.
    5. 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.
    6. Golmohammadi, Amirmohsen & Hassini, Elkafi, 2019. "Capacity, pricing and production under supply and demand uncertainties with an application in agriculture," European Journal of Operational Research, Elsevier, vol. 275(3), pages 1037-1049.
    7. Chen, J.J. & Wu, Q.H. & Zhang, L.L. & Wu, P.Z., 2017. "Multi-objective mean–variance–skewness model for nonconvex and stochastic optimal power flow considering wind power and load uncertainties," European Journal of Operational Research, Elsevier, vol. 263(2), pages 719-732.
    8. Zheng Liu & Qi Xu & Kun Yang, 2018. "Optimal Independent Pricing Strategies of Dual-Channel Supply Chain Based on Risk-Aversion Attitudes," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-17, April.
    9. Taheri, S. Saeid & Kazempour, Jalal & Seyedshenava, Seyedjalal, 2017. "Transmission expansion in an oligopoly considering generation investment equilibrium," Energy Economics, Elsevier, vol. 64(C), pages 55-62.
    10. 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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