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The value of rolling-horizon policies for risk-averse hydro-thermal planning


  • Guigues, Vincent
  • Sagastizábal, Claudia


We consider the optimal management of a hydro-thermal power system in the mid and long terms. From the optimization point of view, this amounts to a large-scale multistage stochastic linear program, often solved by combining sampling with decomposition algorithms, like stochastic dual dynamic programming. Such methodologies, however, may entail prohibitive computational time, especially when applied to a risk-averse formulation of the problem. We propose instead a risk-averse rolling-horizon policy that is nonanticipative, feasible, and time consistent. The policy is obtained by solving a sequence of risk-averse problems with deterministic constraints for the current time step and future chance and CVaR constraints.

Suggested Citation

  • Guigues, Vincent & Sagastizábal, Claudia, 2012. "The value of rolling-horizon policies for risk-averse hydro-thermal planning," European Journal of Operational Research, Elsevier, vol. 217(1), pages 129-140.
  • Handle: RePEc:eee:ejores:v:217:y:2012:i:1:p:129-140
    DOI: 10.1016/j.ejor.2011.08.017

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    References listed on IDEAS

    1. Andrieu, L. & Henrion, R. & Römisch, W., 2010. "A model for dynamic chance constraints in hydro power reservoir management," European Journal of Operational Research, Elsevier, vol. 207(2), pages 579-589, December.
    2. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    3. Shapiro, Alexander, 2011. "Analysis of stochastic dual dynamic programming method," European Journal of Operational Research, Elsevier, vol. 209(1), pages 63-72, February.
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    Cited by:

    1. Bertazzi, Luca & Maggioni, Francesca, 2018. "A stochastic multi-stage fixed charge transportation problem: Worst-case analysis of the rolling horizon approach," European Journal of Operational Research, Elsevier, vol. 267(2), pages 555-569.
    2. Hohmann, Marc & Warrington, Joseph & Lygeros, John, 2020. "A moment and sum-of-squares extension of dual dynamic programming with application to nonlinear energy storage problems," European Journal of Operational Research, Elsevier, vol. 283(1), pages 16-32.
    3. Reus, Lorenzo & Pagnoncelli, Bernardo & Armstrong, Margaret, 2019. "Better management of production incidents in mining using multistage stochastic optimization," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    4. Frans J. C. T. Ruiter & Aharon Ben-Tal & Ruud C. M. Brekelmans & Dick Hertog, 2017. "Robust optimization of uncertain multistage inventory systems with inexact data in decision rules," Computational Management Science, Springer, vol. 14(1), pages 45-66, January.
    5. V. Guigues & C. Sagastizábal & J. P. Zubelli, 2014. "Robust Management and Pricing of Liquefied Natural Gas Contracts with Cancelation Options," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 179-198, April.
    6. Jiang, Ruiwei & Zhang, Muhong & Li, Guang & Guan, Yongpei, 2014. "Two-stage network constrained robust unit commitment problem," European Journal of Operational Research, Elsevier, vol. 234(3), pages 751-762.
    7. W. Ackooij & X. Warin, 2020. "On conditional cuts for stochastic dual dynamic programming," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 8(2), pages 173-199, June.
    8. Vincent Guigues, 2014. "SDDP for some interstage dependent risk-averse problems and application to hydro-thermal planning," Computational Optimization and Applications, Springer, vol. 57(1), pages 167-203, January.
    9. Thomas Kallabis, "undated". "Rolling-horizon optimization as a speed-up method - assessment using the electricity system model JMM," EWL Working Papers 2006, University of Duisburg-Essen, Chair for Management Science and Energy Economics.


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