Open Access
Review
Numéro
Sci. Tech. Energ. Transition
Volume 78, 2023
Numéro d'article 31
Nombre de pages 15
DOI https://doi.org/10.2516/stet/2023026
Publié en ligne 31 octobre 2023
  • Fleten S.-E., Kristoffersen T.K. (2008) Short-term hydropower production planning by stochastic programming, Comput. Oper. Res. 35, 8, 2656–2671. [CrossRef] [Google Scholar]
  • Labadie J.W. (2004) Optimal operation of multireservoir systems: state-of-the-art review, J. Water Resour. Plan. Manag. 130, 2, 93–111. [CrossRef] [Google Scholar]
  • Tahanan M., van Ackooij W., Frangioni A., Lacalandra F. (2015) Large-scale unit commitment under uncertainty, 4OR 13, 2, 115–171. [CrossRef] [MathSciNet] [Google Scholar]
  • van Ackooij W., Danti Lopez I., Frangioni A., Lacalandra F., Tahanan M. (2018) Large-scale unit commitment under uncertainty: an updated literature survey, Ann. Oper. Res. 271, 1, 11–85. [CrossRef] [MathSciNet] [Google Scholar]
  • Rahmaniani R., Crainic T.G., Gendreau M., Walter W. (2017) The benders decomposition algorithm: a literature review, Eur. J. Oper. Res. 259, 3, 801–817. [CrossRef] [MathSciNet] [Google Scholar]
  • Sen S. (2005) Algorithms for stochastic mixed-integer programming models, in: Handbooks in Operations Research and Management Science, vol. 12, Elsevier, pp. 515–558. [CrossRef] [Google Scholar]
  • Shapiro A. (2011) Analysis of stochastic dual dynamic programming method, Eur. J. Oper. Res. 209, 1, 63–72. [CrossRef] [Google Scholar]
  • van Ackooij W., Malick J. (2016) Decomposition algorithm for large-scale two-stage unitcommitment, Ann. Oper. Res. 238, 1, 587–613. [CrossRef] [MathSciNet] [Google Scholar]
  • Carpentier P.-L., Gendreau M., Bastin F. (2013) Long-term management of a hydro electric multireservoir system under uncertainty using the progressive hedging algorithm, Water Resour. Res. 49, 5, 2812–2827. [CrossRef] [Google Scholar]
  • Carpentier P., Chancelier J.-P., Leclère V., Pacaud F. (2018) Stochastic decomposition applied to large-scale hydro valleys management, Eur. J. Oper. Res. 270, 3, 1086–1098. [CrossRef] [MathSciNet] [Google Scholar]
  • van Ackooij W., d’Ambrosio C., Thomopulos D., Trindade R.S. (2021) Decomposition and shortest path problem formulation for solving the hydro unit commitment and scheduling in a hydro valley, Eur. J. Oper. Res. 291, 3, 935–943. [CrossRef] [MathSciNet] [Google Scholar]
  • Ahmed S., Tawarmalani M., Sahinidis N.V. (2004) A finite branch-and-bound algorithm for two-stage stochastic integer programs, Math. Program. 100, 2, 355–377. [CrossRef] [MathSciNet] [Google Scholar]
  • Carøe C.C., Tind J. (1998) L-shaped decomposition of two-stage stochastic programs with integer recourse, Math. Program. 83, 451–464. [CrossRef] [MathSciNet] [Google Scholar]
  • Gade D., Küçükyavuz S., Sen S. (2014) Decomposition algorithms with parametric Gomory cuts for two-stage stochastic integer programs, Math. Program. 144, 1–2, 39–64. [CrossRef] [MathSciNet] [Google Scholar]
  • Laporte G., Louveaux F.V. (1993) The integer L-shaped method for stochastic integer programs with complete recourse, Oper. Res. Lett. 13, 3, 133–142. [CrossRef] [MathSciNet] [Google Scholar]
  • Zou J., Ahmed S., Sun X.A. (2019) Stochastic dual dynamic integer programming, Math. Program. 175, 461–502. [CrossRef] [MathSciNet] [Google Scholar]
  • El Amri R., Helbert C., Zuniga M.M., Prieur C., Sinoquet D. (2020) Set inversion under functional uncertainties with joint meta-models (working paper or preprint). [Google Scholar]
  • Antoniadis A., Helbert C., Prieur C., Viry L. (2012) Spatio-temporal meta modeling for west African monsoon, Environmetrics 23, 1, 24–36. [CrossRef] [MathSciNet] [Google Scholar]
  • Nanty S., Helbert C., Marrel A., Pérot N., Prieur C. (2016) Sampling, metamodelling and sensitivity analysis of numerical simulators with functional stochastic inputs, SIAM/ASA J. Uncertain. Quantif. 4, 1, 636–659. [CrossRef] [MathSciNet] [Google Scholar]
  • Nanty S., Helbert C., Marrel A., Pérot N., Prieur C. (2017) Uncertainty quantification for functional dependent random variables, Comput. Stat. 32, 2, 559–583. [CrossRef] [MathSciNet] [Google Scholar]
  • Piron V., Bontron G., Pochat M. (2015) Operating a hydropower cascade to optimize energy management, Int. J. Hydropower Dams 22, 5. [Google Scholar]
  • Bellier J., Zin I., Bontron G. (2018) Generating coherent ensemble forecasts after hydrological postprocessing: adaptations of ECC-based methods, Water Resour. Res. 54, 8, 5741–5762. [CrossRef] [Google Scholar]
  • Celie S., Bontron G., Ouf D., Pont E. (2019) Apport de l’expertise dans la prévision hydro-météorologique opérationnelle, La Houille Blanche 2, 55–62. [CrossRef] [EDP Sciences] [Google Scholar]
  • Blair C.E., Jeroslow R.G. (1977) The value function of a mixed integer program: I, Discrete Math. 19, 2, 121–138. [CrossRef] [MathSciNet] [Google Scholar]
  • Haneveld K., Van der Vlerk M.H. (2020) Stochastic programming, Springer. [Google Scholar]
  • Ralphs T.K., Hassanzadeh A. (2014) On the value function of a mixed integer linear optimization problem and an algorithm for its construction. COR@ L Technical Report 14T-004. [Google Scholar]
  • Bellier J., Zin I., Siblot S., Bontron G. (2016) Probabilistic flood forecasting on the Rhone River: evaluation with ensemble and analogue-based precipitation forecasts, in: E3S Web of Conferences, vol. 7, EDP Sciences, p. 18011. [CrossRef] [EDP Sciences] [Google Scholar]
  • Lorenz E.N. (1969) Atmospheric predictability as revealed by naturally occurring analogues, J. Atmos. Sci. 26, 4, 636–646. [CrossRef] [Google Scholar]
  • Gneiting T., Raftery A.E. (2007) Strictly proper scoring rules, prediction, and estimation, J. Am. Stat. Assoc. 102, 477, 359–378. [CrossRef] [Google Scholar]
  • Hersbach H. (2000) Decomposition of the continuous ranked probability score for ensemble prediction systems, Weather Forecast. 15, 5, 559–570. [CrossRef] [Google Scholar]
  • Matheson J.E., Winkler R.L. (1976) Scoring rules for continuous probability distributions, Manag. Sci. 22, 10, 1087–1096. [CrossRef] [Google Scholar]
  • Santner T.J., Williams B.J., Notz W.I., Williams B.J. (2003) The design and analysis of computer experiments, vol. 1, Springer. [CrossRef] [Google Scholar]
  • De Boor C. (1978) A practical guide to splines, vol. 27, Springer-verlag, New York, p. 545. [Google Scholar]
  • Jolliffe I. (2005) Principal component analysis, in: Encyclopedia of Statistics in Behavioral Science, Wiley. [Google Scholar]
  • Ramsay J.O., Silverman B.W. (2002) Applied functional data analysis: methods and case studies, vol. 77, Springer. [CrossRef] [Google Scholar]
  • Torrence C., Compo G.P. (1998) A practical guide to wavelet analysis, Bull. Am. Meteorol. Soc. 79, 1, 61–78. [CrossRef] [Google Scholar]

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