Ce travail contribue aux efforts de l'Union Européenne pour réduire les émissions de CO2. Son objectif est d'aider les industries produisant de la chaleur fatale à récupérer cette énergie perdue, d'augmenter sa température et de la réutiliser in situ. Les transformateurs de chaleur (Absorption Heat Transformers ou AHT), machines à absorption consommant très peu d'électricité, sont alors ici étudiés. Les AHTs existants rencontrent des problèmes comme la corrosion, la cristallisation, la toxicité et les niveaux de pression éloignés de la pression atmosphérique. Ceux-ci sont causés par les fluides conventionnels (Eau/LiBr et Ammoniaque/Eau) et s'aggravent à des températures supérieures à 120°C. Des modèles de conception ainsi que des solutions techniques, applicables avec tous mélanges de fluides organiques, sont alors proposés dans cette thèse. Ces modèles sont validés avec des données de la littérature et implémentés dans des outils d'aide à la décision.Tout d'abord, un modèle de sélection de paires de fluides organiques (parmi une liste de fluides) est développé. Les contraintes prises en compte sont, entre autres, les types et les profils de températures des sources et puits de chaleur, et les propriétés du fluide. Pour chaque type de fluide, la méthode la plus adaptée au calcul des propriétés physiques des fluides est choisie.En second lieu, pour effectuer la séparation des 2 constituants du mélange de fluides organiques, le générateur (composant recevant la chaleur fatale) et le condenseur de l'AHT sont fusionnés pour former une colonne de distillation. Un modèle d'une colonne de distillation nommée « hybride » est alors développé en adaptant la méthode de Ponchon-Savarit et en la combinant avec la méthode ETD (Equal Thermodynamic Distance). Cette colonne associe les avantages des 2 types de colonnes adiabatiques et diabatiques. Elle allie réduction de production d'entropie et meilleure exploitation des sources de chaleur à températures glissantes. La conception mécanique de la colonne hybride est aussi incluse.Troisièmement, pour atteindre la température théorique maximale du mélange de fluide déjà choisi, l'absorbeur de l'AHT (où la chaleur à haute température est libérée) est divisé en sections adiabatiques suivies par des sections diabatiques. De plus, les modèles détaillés des colonnes à bulles (fonctionnant en co-courant ou en contre-courant) ainsi que de la colonne à garnissage sont présentés et comparés entre eux.Les principaux résultats de ces travaux consistent en une nouvelle méthodologie de choix de fluides organiques pouvant remplacer les mélanges classiques surtout à températures élevées (supérieures à 130 °C). En ce qui concerne la colonne de distillation, il est montré que la colonne adiabatique constitue un meilleur choix lorsqu'une source de chaleur latente est disponible tandis qu'avec une source de chaleur sensible, la colonne hybride engendre moins de pertes exergétiques. En passant à l'absorbeur, le nouveau mode d'opération de celui-ci permet à l'utilisateur d'atteindre des températures plus élevées que celles réalisées avec les technologies actuellement disponibles. Enfin, les modèles développés permettent de choisir les technologies de distillation (adiabatique, diabatique ou hybride) et d'absorption (colonne à bulles ou à garnissage) les plus appropriées en s'adaptant à différentes problématiques industrielles. / This work is part of the European union efforts to reduce its CO2 emissions. It aims to assist any waste heat producing industry in recuperating this lost thermal energy, pumping it to higher temperature levels and reusing it on site. Absorption Heat Transformers (AHT), that consume little electricity, are used for this task. Current AHT problems such as corrosion, crystallization, toxicity and inconvenient pressure levels are caused by conventionally used H2O/LiBr and NH3/ H2O working fluids and get worse at temperatures exceeding 120°C. Potential solutions are thus suggested. According to them, models are developed; they are all able to operate with any organic mixture and are customized to accompany the industrialist from start to finish. These solutions were validated by comparing them with literature data and are implemented into several tools.Firstly, a model selects the optimal organic binary mixture -among a list of fluids- in terms of the real case application's constraints: Heat transfer fluids used, Heat source's and heat sink's types and temperature profiles, mixtures transport properties among other parameters. Suitable thermodynamic model is selected for different fluid group types.Secondly, in order to separate the 2 components of the chosen mixture of organic compounds, the AHT generator (component which receives waste heat) is merged with the AHT condenser thus forming a distillation column. A “hybrid column” is designed by modifying the Ponchon-Savarit method and combining it with the Equal Thermodynamic Distance (ETD) method. This new column associates the best features of the two columns. It reduces entropy production rates and best exploits temperature gliding heat sources. Mechanical design for the hybrid column is also included.Thirdly, to ensure that the maximum theoretical temperature of the working fluid is reached, the AHT absorber (where high temperature heat is released) is divided into consecutive adiabatic parts followed by diabatic ones. Detailed Models for co-current and counter-current bubble columns as well as packing columns are presented and compared.Main results consist in a selection methodology of organic compounds mixtures, capable of replacing conventional ones specially at temperatures higher than 130 °C. It's also shown that adiabatic columns are better options when latent type heat sources are available while hybrid columns lose less exergy when used with sensible heat sources. As for the absorber, the new operating mode provides the user with higher temperatures than currently reached by available technologies. Finally, using the developed models, tailored and most suitable distillation (adiabatic, diabatic or hybrid columns) and absorber (bubble or packing columns) technologies can be proposed depending on the industrial specific cases and requirements.

[pt] Este trabalho tem como objetivo estudar estratégias de Controle Preditivo baseado em Modelo Não-Linear (NMPC) aplicadas a uma coluna de destilação despropanizadora simulada. Essas colunas são empregadas em unidades de processamento de gás natural (UPGNs) para a separação do produto propano do butano. Colunas de destilação possuem características particularmente desafiadoras sob o ponto de vista de controle, como: não-linearidades, grandes constantes de tempo, atraso, restrições de variáveis e inversão do sinal de ganho estático. Como as medidas de composição frequentemente possuem atrasos e dados esparsos, os sistemas de controle convencionais não são capazes de controlar a composição diretamente e possuem dificuldade em manter os produtos dentro das especificações. Contudo, controladores baseados em modelo possuem a habilidade de prever a composição através do modelo interno do processo, além de serem capazes de lidar com restrições. Na literatura, nenhuma aplicação do modelo de Hammerstein modificado para coluna de destilação ou para sistemas multivariáveis foi encontrada, sendo esta uma novidade. Desta forma, foram estudadas três estratégias de controle: controle PID tradicional, NMPC com modelo de Hammerstein modificado (H-NMPC) e NMPC com modelo por Redes Neurais (NN-NMPC). O sistema estudado foi identificado de forma a se obter valores numéricos adequados aos parâmetros dos modelos. A identificação dos parâmetros dos modelos e os algoritmos de NMPC foram implementados no ambiente MATLAB. A coluna de destilação foi simulada usando o Aspen Plus Dynamics. Como resultado, o H-NMPC teve o melhor desempenho de controle ao rastrear diferentes trajetórias de referência, a desacoplar as variáveis controladas e a rejeitar os distúrbios. Além disso, esta apresentou maior rapidez computacional comparado com a estratégia NNNMPC. / [en] This work aims to study strategies of Nonlinear Model Predictive Control (NMPC) applied to a simulated depropanizer distillation column. These columns are used in natural gas processing units (NGPUs) for the separation of the product propane from butane. Distillation columns have particularly challenging features from the control point of view, such as: nonlinearities, large time constants, delay, variable constraints and static gain signal inversion. Because compositional measures often have delays and sparse data, conventional control systems are not able to control composition directly and have difficulty keeping products within specifications. However, model-based controllers predict composition through the internal process model, besides being able to handle constraints. In the literature, no applications of the modified Hammerstein model for distillation column or multivariable systems was found, so this is a novelty. Therefore, three control strategies were studied: traditional PID control, NMPC with modified Hammerstein model (H-NMPC) and NMPC with neural network model (NN-NMPC). The studied system was identified in order to obtain adequate numerical values of the model parameters. The model identification and the NMPC algorithms were implemented in the MATLAB environment. The distillation column was simulated using Aspen Plus Dynamics. As a result, the H-NMPC provided better control performance for different setpoint tracking, control variables decoupling, and disturbance rejection. Furthermore, it presented faster computational speed compared to NN-NMPC.

The thesis contains information about the design of pressure vessels and describes their individual parts. It is mentioned production of individual parts and the process including assembly parts in one unit. The thesis includes options of control and testing of pressure vessels. It is described kinds of built-ins of distillation column and the basic principles and types of distillation. It is created stress analysis of pressure vessels parts according to ČSN EN 13 445 – 3, and also stress analysis of the selected part of column by using FEM. Mechanical drawing of distillation column is part of the thesis.