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Decomposition algorithm for large-scale two-stage unit-commitment

Author

Listed:
  • Wim Ackooij

    (EDF R&D, OSIRIS)

  • Jérôme Malick

    (CNRS)

Abstract

Everyday, electricity generation companies submit a generation schedule to the grid operator for the coming day; computing an optimal schedule is called the unit-commitment problem. Generation companies can also occasionally submit changes to the schedule, that can be seen as intra-daily incomplete recourse actions. In this paper, we propose a two-stage formulation of unit-commitment, wherein both the first and second stage problems are full unit-commitment problems. We present a primal-dual decomposition approach to tackle large-scale instances of these two-stage problems. The algorithm makes extensive use of warm-started bundle algorithms, and requires no specific knowledge of the underlying technical constraints. We provide an analysis of the theoretical properties of the algorithm, as well as computational experiments showing the interest of the approach for real-life large-scale unit-commitment instances.

Suggested Citation

  • Wim Ackooij & Jérôme Malick, 2016. "Decomposition algorithm for large-scale two-stage unit-commitment," Annals of Operations Research, Springer, vol. 238(1), pages 587-613, March.
  • Handle: RePEc:spr:annopr:v:238:y:2016:i:1:d:10.1007_s10479-015-2029-8
    DOI: 10.1007/s10479-015-2029-8
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    References listed on IDEAS

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    1. Birge, John R. & Louveaux, Francois V., 1988. "A multicut algorithm for two-stage stochastic linear programs," European Journal of Operational Research, Elsevier, vol. 34(3), pages 384-392, March.
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    Cited by:

    1. Wim Ackooij & Nicolas Lebbe & Jérôme Malick, 2017. "Regularized decomposition of large scale block-structured robust optimization problems," Computational Management Science, Springer, vol. 14(3), pages 393-421, July.
    2. Clara Lage & Claudia Sagastizábal & Mikhail Solodov, 2020. "Multiplier Stabilization Applied to Two-Stage Stochastic Programs," Post-Print halshs-02900862, HAL.
    3. Clara Lage & Claudia Sagastizábal & Mikhail Solodov, 2020. "Multiplier Stabilization Applied to Two-Stage Stochastic Programs," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02900862, HAL.
    4. Clara Lage & Claudia Sagastizábal & Mikhail Solodov, 2020. "Multiplier Stabilization Applied to Two-Stage Stochastic Programs," Documents de travail du Centre d'Economie de la Sorbonne 20010, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    5. W. Ackooij & A. Frangioni & W. Oliveira, 2016. "Inexact stabilized Benders’ decomposition approaches with application to chance-constrained problems with finite support," Computational Optimization and Applications, Springer, vol. 65(3), pages 637-669, December.
    6. Alexander Franz & Julia Rieck & Jürgen Zimmermann, 2019. "Fix-and-optimize procedures for solving the long-term unit commitment problem with pumped storages," Annals of Operations Research, Springer, vol. 274(1), pages 241-265, March.
    7. Pedro Borges, 2022. "Cut-sharing across trees and efficient sequential sampling for SDDP with uncertainty in the RHS," Computational Optimization and Applications, Springer, vol. 82(3), pages 617-647, July.
    8. Clara Lage & Claudia Sagastizábal & Mikhail Solodov, 2019. "Multiplier Stabilization Applied to Two-Stage Stochastic Programs," Journal of Optimization Theory and Applications, Springer, vol. 183(1), pages 158-178, October.
    9. Wim van Ackooij & Welington de Oliveira & Yongjia Song, 2018. "Adaptive Partition-Based Level Decomposition Methods for Solving Two-Stage Stochastic Programs with Fixed Recourse," INFORMS Journal on Computing, INFORMS, vol. 30(1), pages 57-70, February.
    10. 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.

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