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  1. Optimization under uncertainty with a surrogate model for the short-term production planning of a hydropower cascade combined with variable energy sources ; Optimisation sous incertitudes par métamodèle pour la planification à court terme de la production conjointe d'une chaîne hydroélectrique et d'actifs de production variable
    Erschienen: 2022
    Verlag:  HAL CCSD

    Short-term production planning of a hydropower cascade combined with variable energy sources is an optimization problem. The hydropower production plan is constructed within a time horizon of a few days to comply with operational requirements and to... mehr

     

    Short-term production planning of a hydropower cascade combined with variable energy sources is an optimization problem. The hydropower production plan is constructed within a time horizon of a few days to comply with operational requirements and to maximize revenues obtained by selling the total production from all energy sources on the day-ahead market and by penalizing imbalances.This PhD thesis focuses on the optimization problem considering data uncertainty on water inflows, electricity prices and variable generation, modeled by a finite set of multivariate scenarios. The proposed optimization problem in the stochastic framework is then written with a two-stage stochastic dynamic mixed-integer linear programming formulation.Since computation time is a crucial issue for an operational use, the optimization problem is solved by replacing the value function of the second stage with a surrogate model fitted by supervised learning during a pre-processing step. The surrogate model is fitted on input data that are simplified by specific approaches. The domain of the input data related to the decision variables of the first stage is first estimated by analog-based sampling, and the functional inputs are reduced by principal components analysis. The learning data set can then be obtained from a design of experiments using latin hypercube sampling. Several linear models are finally proposed for the surrogate model.The proposed methodology is tested on a real but simplified case study. The surrogate model obtained by linear regression on the reduced inputs provides acceptable performance, and it can be used to get a solution to the optimization problem in the stochastic framework. Since variable generation is not considered in the case study, the stochastic framework provides, however, minor profit compared to the deterministic framework. Besides, computation time is not compatible with an operational use without distributed computing. Several research tracks are then proposed to improve the methodology. A validation ...

     

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  2. Inverse problems and local resonances in irregular mechanical waveguides ; Problèmes inverses et résonances locales dans les guides d’ondes mécaniques irréguliers
    Erschienen: 2022
    Verlag:  HAL CCSD

    Localization and reconstruction of defects in waveguides are crucial in the nondestructive evaluation of structures like pipelines, optics fibers, nuclear power plant conduits, or even ship hulls. This thesis aims to understand waves propagation in... mehr

     

    Localization and reconstruction of defects in waveguides are crucial in the nondestructive evaluation of structures like pipelines, optics fibers, nuclear power plant conduits, or even ship hulls. This thesis aims to understand waves propagation in waveguides from a mathematical point of view to design new efficient methods to detect and reconstruct potential waveguides defects. To reproduce the existing experimental setups, we use multi-frequency data with frequencies sometimes close to resonant ones. Far from the resonant frequencies, we prove that the defects reconstruction is equivalent to a Fourier inversion from partial data, and we provide a stable reconstruction method working for small defects. On the other hand, mathematical equations are not well-posed near resonant frequencies, but waves seem very sensitive to potential defects. Drawing a parallel with quantum mechanics, we provide an asymptotic approximation of these waves as Airy functions when the width of the waveguide slowly varies. Using these approximations, we develop a precise method based on the shape of Airy functions to reconstruct width defects in waveguides. ; La détection et la reconstruction de défauts dans les guides d’ondes sont un enjeu contemporain important pour contrôler l’état de structures diverses allant des oléoducs aux fibres optiques, en passant par les conduits de centrales nucléaires ou les coques de navires. Cette thèse a pour but de mieux comprendre d’un point de vue mathématique la propagation des ondes en guide d’onde, pour pouvoir ensuite proposer des méthodes efficaces pour détecter et reconstruire avec précision d’éventuels défauts. Pour modéliser au mieux les dispositifs expérimentaux disponibles, on choisit ici d’utiliser des ondes se propageant à des fréquences variables et parfois voisines des fréquences de résonances. Si les fréquences sont éloignées des résonances, on montre que la reconstruction de défaut s’apparente à de l’inversion de Fourier avec données partielles, ce qui permet de reconstruire de ...

     

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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Französisch
    Medientyp: Dissertation
    Format: Online
    Übergeordneter Titel: https://theses.hal.science/tel-03813494 ; Autre. Université de Lyon, 2022. Français. ⟨NNT : 2022LYSEC026⟩
    Schlagworte: Waveguides; Inverse problems; Non-destructing testing; Wave propagation; Mutli-frequency data; Helmholtz equation; Elastic displacement equation; Locally resonances; Guides d’ondes; Problèmes inverses; Contrôle non destructif; Propagation des ondes; Données multi-fréquencielles; Équation de Helmholtz; Équation du déplacement élastique; Résonances locales; [SPI.OTHER]Engineering Sciences [physics]/Other
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    info:eu-repo/semantics/OpenAccess