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Stochastic dual dynamic programming applied to nonconvex hydrothermal models

S. Cerisola, J.M. Latorre, A. Ramos

European Journal of Operational Research Vol. 218, nº. 3, pp. 687 - 697

Summary:

In this paper we apply stochastic dual dynamic programming decomposition to a nonconvex multistage stochastic hydrothermal model where the nonlinear water head effects on production and the nonlinear dependence between the reservoir head and the reservoir volume are modeled. The nonconvex constraints that represent the production function of a hydro plant are approximated by McCormick envelopes. These constraints are split into smaller regions and the McCormick envelopes are used for each region. We use binary variables for this disjunctive programming approach and solve the problem with a decomposition method. We resort to a variant of the L-shaped method for solving the MIP subproblem with binary variables at any stage inside the stochastic dual dynamic programming algorithm. A realistic large-scale case study is presented.


Keywords: Programming: Stochastic; Integer; Benders decomposition; Lagrangean relaxation; Stochastic Dual Dynamic Programming; Production/scheduling: planning


JCR Impact Factor and WoS quartile: 2,038 - Q1 (2012); 6,000 - Q1 (2023)

DOI reference: DOI icon https://doi.org/10.1016/j.ejor.2011.11.040

Published on paper: May 2012.

Published on-line: December 2011.



Citation:
S. Cerisola, J.M. Latorre, A. Ramos, Stochastic dual dynamic programming applied to nonconvex hydrothermal models. European Journal of Operational Research. Vol. 218, nº. 3, pp. 687 - 697, May 2012. [Online: December 2011]


    Research topics:
  • *Medium-Term Tactical Planning
  • *Long-Term Strategic Analysis

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