Energy demand for buildings has been rising during recent years. Increasing building energy consumption has caused many energy-related problems and environmental issues. The on-site community energy system application is a promising way of providing energy for buildings. Community energy system usage reduces the primary energy consumption and environmental effects of greenhouse gas (GHG) emissions compared to the implementation of the stand-alone energy systems. Furthermore, due to the increase in electricity price and shortage of fossil fuel resources, renewable energies and energy storage technologies could be great alternative solutions to solve energy-related problems. Generally, the energy system might include various technologies such as internal combustion engine, heat recovery system, boiler, thermal storage tank, battery, absorption chiller, ground source heat pump, heating coil, electric chiller, solar photovoltaics (PV) and solar thermal collectors, and seasonal thermal energy storage. The economic, technical and environmental impacts of energy systems depend on the system design and operational strategy. The focus of this thesis is to propose unified frameworks, including the mathematical formulation of all of the components to determine the optimal energy system configuration, the optimal size of each component, and optimal operating strategy. The proposed methodologies address the problems related to the optimal design of the energy system for both deterministic and stochastic cases. By the use of the proposed frameworks, the design of the energy system is investigated for different specified levels of GHG emissions ratio, and the purpose is to minimize the annual total cost. To account for uncertainties and to reduce the computational times and maintain accuracy, a novel strategy is developed to produce scenarios for the stochastic problem. System design is carried out to minimize the annual total cost and conditional value at risk (CVaR) of emissions for the confidence level of 95%. The results demonstrate how the system size changes due to uncertainty and as a function of the operational GHG emissions ratio. It is shown that with the present-day technology (without solar technologies and seasonal storage), the lowest amount of GHG emissions ratio is 37%. This indicates the need for significant technological development to overcome that ratio to be 10% of stand-alone systems. This thesis introduces novel performance curves (NPC) for determining the optimal operation of the energy system. By the use of this approach, it is possible to identify the optimal operation of the energy system without solving complex optimization procedures. The application of the proposed NPC strategy is investigated for various case studies in different locations. The usage of the proposed strategy leads to the best-operating cost-saving and operational GHG savings when compared to other published approaches. It has shown that other strategies are special (not always optimal) cases of the NPC strategy. Based on the extensive literature review, it is found that it is exceptionally complicated to apply the previously proposed models of seasonal thermal energy storage in optimization software. Besides, the high computational time is required to obtain an optimum size and operation of storage from an optimization software. This thesis also proposes a new flexible semi-analytical, semi-numerical methodology to model the heat transfer process of the borehole thermal energy storage to solve the above challenges. The model increases the flexibility of the storage operation since the model can control the process of the storage by also deciding the appropriate storage zone for charging and discharging. / Thesis / Doctor of Engineering (DEng)

Ce travail de thèse constitue le prolongement direct des travaux de thèse Chachuat (2001) sur l'optimisation dynamique et la commande optimale des stations de traitement de petite taille. L'objectif est d'aller plus loin en s'intéressant aux dimensionnement et fonctionnement optimaux des stations de traitement des eaux usées de toute taille. Ainsi, dans une première étape, l'optimisation des stations de traitement de petite taille a été abordée. Contrairement à ce qui a été fait jusqu'à maintenant : (i) l'aération n'est plus alternée, mais continue, (ii) le décanteur n'est plus considéré comme parfait, mais son fonctionnement est modélisé à l'aide d'une série de 10 couches de décantation, (iii) la méthode d'optimisation développée est fondée sur la méthode des sensibilités implémentée au sein du logiciel de simulation et optimisation dynamiques gProms, utilisé dans toute la thèse. L'influence du modèle du décanteur sur la minimisation de l'énergie d'aération a été particulièrement analysée. Dans une deuxième étape, les stations de traitement de grande taille sont considérées. Plus spécifiquement, le modèle benchmark développé par le réseau européen COST a été utilisé pour décrire leur fonctionnement. Un « foreignobject » a été développé pour que la simulation et l'optimisation du fonctionnement de ces stations soient possibles sous gProms. L'optimisation a notamment montré que la consommation d'énergie d'aération pouvait être réduite d'au moins de 30% par rapport au fonctionnement actuel de ces stations. Dans une troisième étape, l'optimisation du dimensionnement des stations de traitement de grande taille a été étudiée. Une superstructure a ainsi été définie avec plusieurs (cinq) réacteurs et un décanteur. Toutes les possibilités de recyclage et de court-circuit entre les réacteurs d'une part et entre les réacteurs et le décanteur d'autre part sont prises en compte. L'objectif était de déterminer la meilleure structure et les valeurs optimales des volumes des réacteurs qui permettent de minimiser le coût total tout en respectant les contraintes réglementaires sur les rejets.Par ailleurs, une optimisation multicritère de la station optimale résultante a été réalisée. Elle a permis de déterminer l'ensemble de Pareto des solutions qui minimisent la consommation énergétique (d'aération et de pompage) et maximisent la qualité de l'effluent. La quatrième et dernière partie de ce travail s'intéresse à la modélisation, simulation et optimisation de la station de traitement de Verulam près de Durban en Afrique du Sud. Des mesures expérimentales ont été réalisées sur cette station et le modèle ASM1 a été utilisé pour décrire son fonctionnement. Une analyse d'estimabilité des paramètres a été d'abord réalisée pour déterminer les paramètres du modèle qui peuvent être estimés à partir des mesures expérimentales disponibles. Les paramètres estimables ont ensuite été identifiés à l'aide de gProms. Le modèle ainsi identifié a été validé et ensuite utilisé pour optimiser le fonctionnement énergétique de cette station / This work is a direct extension of the PhD thesis of Chachuat (2001) on dynamic optimization and optimal control of small size wastewater treatment plants. The objective is to go further by focusing on optimal design and operation of wastewater treatment plants of any size. Thus, in a first part, optimization of small size wastewater treatment plants was studied. Contrary to what has been done so far: (i) the aeration is no longer alternating, but continuous, (ii) the settler is not considered perfect, but its operation is modeled using a series of 10 sedimentation layers, (iii) the optimization approach developed is based on the method of sensitivities implemented wthin the dynamic simulation and optimization software gProms, used throughout this work. The influence of the settler model on the minimization of aeration energy was particularly investigated. In a second part , the large size treatment plants are considered . More specifically, the benchmark model developed by the European network COST was used to describe their operation. A "foreign object" was developed in order to make the simulation and optimization of these plants possible using gProms. The optimisation showed that the aeration energy consumption could be reduced by at least 30 % compared to the current operation of these plants . In a third part, the optimization of the design of the wastewater treatment plant was studied. A superstructure has been defined with several (five) reactors and a settler. All the possibilities of recycling and by-passes between the reactors on the one hand and between the reactors and the settler on the other are considered. The objective was to determine the best structure and the optimal values of the reacter volumes that minimize the net present value while respecting the regulatory constraints. On the other hand, a multi-objective optimization problems of the treatment plant was carried out. It allawed to determine the Pareto set of solutions that minimize the energy consumption (pumping and aeration) and maximize the effluent quality. The fourth and last part of this work focuses on modeling, simulation and optimization of the treatment plant of the city of Verulam in the area of Durban in South Africa. Experimental measurements were carried out on the plant and the ASM1 model was used to describe its operation. An estimability analysis was first performed in order to determine the model parameters that can be estimated from the available experimental measurements . The estimable parameters were then identified using gProms . The identified model was validated and then used to optimize the energy function of this plant