abstract: A model is presented for real-time, river-reservoir operation systems. It epitomizes forward-thinking and efficient approaches to reservoir operations during flooding events. The optimization/simulation includes five major components. The components are a mix of hydrologic and hydraulic modeling, short-term rainfall forecasting, and optimization and reservoir operation models. The optimization/simulation model is designed for ultimate accessibility and efficiency. The optimization model uses the meta-heuristic approach, which has the capability to simultaneously search for multiple optimal solutions. The dynamics of the river are simulated by applying an unsteady flow-routing method. The rainfall-runoff simulation uses the National Weather Service NexRad gridded rainfall data, since it provides critical information regarding real storm events. The short-term rainfall-forecasting model utilizes a stochastic method. The reservoir-operation is simulated by a mass-balance approach. The optimization/simulation model offers more possible optimal solutions by using the Genetic Algorithm approach as opposed to traditional gradient methods that can only compute one optimal solution at a time. The optimization/simulation was developed for the 2010 flood event that occurred in the Cumberland River basin in Nashville, Tennessee. It revealed that the reservoir upstream of Nashville was more contained and that an optimal gate release schedule could have significantly decreased the floodwater levels in downtown Nashville. The model is for demonstrative purposes only but is perfectly suitable for real-world application. / Dissertation/Thesis / Doctoral Dissertation Civil Engineering 2015

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Les systèmes complexes à longue durée de service sont des systèmes de grande taille qui ont généralement un comportement stochastique. Dans cette thèse, nous étudions, particulièrement, un type de ces systèmes : le système de vélos en libre-service. Le principe de fonctionnement de ce service de transports est de disposer des vélos dans diverses stations de la ville. Les usagers viennent prendre des vélos pour effectuer un trajet et puis les déposent dans des stations quelconques.Comme la durée d’exploitation de ces systèmes est longue, de nouveaux besoins (par exemple l’attractivité de station) et une dégradation de performance peuvent survenir. Un outil d’aide à la décision est ainsi nécessaire pour analyser et améliorer la performance par des opérations de pilotage (p.ex. changement de la taille de flotte) ou de re-conception (p.ex. changement de la capacité d’une station). L’approche suivie, pour cette finalité, est la modélisation stochastique en utilisant un réseau de files d’attente possédant des files à capacités limitées et un mécanisme de blocage. La méthode de résolution du modèle proposé est définie dans les travaux de Kouvatsos (1994). Notre cas d’étude est un sous-réseau de 20 stations du système Vélib’ de Paris. L’analyse de la performance suite aux changements exogènes et aux opérations d’amélioration (pilotage et re-conception), nous a permis de déduire un ensemble de préconisations qui peuvent améliorer les performances du système. Comme la méthode de résolution de ce modèle possède une complexité importante, nous proposons une méthode d’agrégation des stations pour réduire la taille du problème en ayant des erreurs maîtrisables. Cette méthode est implémentée et évaluée pour un système particulier où tous les paramètres sont homogènes. Enfin, l’étude de cette méthode pour un système non-homogène et d’autres perspectives sont proposées pour étendre ces travaux de recherche. / Complex systems having a long period of service are large scale systems that typically have stochastic behavior. In this thesis, we study, in particular, one type of these systems: the Bike Sharing System. The operating principle of this transport service consists of a fleet of bikes disposed in various stations. The users come to take bicycles to use them for their trip and then bring them back in any stations.As these systems are supposed to operate for long periods, new requirements can overcome (eg. station attractiveness) and performance degradation may occur. A decision support tool is thus required to analyze and improve the performance by control operations (eg. fleet size change) or re-design (eg. changing the capacity of a station).The stochastic modeling approach is used through a network of queues with limited capacity queues and a blocking mechanism. The resolution method of the proposed model is defined in the research work of Kouvatsos (1994).The case study is a sub-network of 20 Vélib's stations in Paris. The performance analysis according to exogenous changes and improvement operations (control and re-design) allowed us to deduce recommendations that can improve the performance of the system.As the method of solving this model has a great complexity, we propose a method of aggregation of the stations to reduce the size of the problem by having controllable errors. This method is implemented and evaluated for a particular system where all the parameters are homogeneous. Finally, the study of this method for a non-homogeneous system and other perspectives are proposed to extend this research work.

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In order to increase the power density, the discontinuous conducting mode (DCM) and small inductance is adopted for high power bidirectional dc-dc converter. The DCM related current ripple is minimized with multiphase interleaved operation. The turn-off loss caused by the DCM induced high peak current is reduced by snubber capacitor. The energy stored in the capacitor needs to be discharged before device is turned on. A complementary gating signal control scheme is employed to turn on the non-active switch helping discharge the capacitor and diverting the current into the anti-paralleled diode of the active switch. This realizes the zero voltage resonant transition (ZVRT) of main switches. This scheme also eliminates the parasitic ringing in inductor current. This work proposes an inductance and snubber capacitor optimization methodology. The inductor volume index and the inductor valley current are suggested as the optimization method for small volume and the realization of ZVRT. The proposed capacitance optimization method is based on a series of experiments for minimum overall switching loss. According to the suggested design optimization, a high power density hardware prototype is constructed and tested. The experimental results are provided, and the proposed design approach is verified. In this dissertation, a general-purposed power stage model is proposed based on complementary gating signal control scheme and derived with space-state averaging method. The model features a third-order system, from which a second-order model with resistive load on one side can be derived and a first-order model with a voltage source on both sides can be derived. This model sets up a basis for the unified controller design and optimization. The Δ-type model of coupled inductor is introduced and simplified to provide a more clearly physical meaning for design and dynamic analysis. These models have been validated by the Simplis ac analysis simulation. For power flow control, a unified controller concept is proposed based on the derived general-purposed power stage model. The proposed unified controller enables smooth bidirectional current flow. Controller is implemented with digital signal processing (DSP) for experimental verification. The inductor current is selected as feedback signal in resistive load, and the output current is selected as feedback signal in battery load. Load step and power flow step control tests are conducted for resistive load and battery load separately. The results indicate that the selected sensing signal can produce an accurate and fast enough feedback signal. Experimental results show that the transition between charging and discharging is very smooth, and there is no overshoot or undershoot transient. It presents a seamless transition for bidirectional current flow. The smooth transition should be attributed to the use of the complementary gating signal control scheme and the proposed unified controller. System simulations are made, and the results are provided. The test results have a good agreement with system simulation results, and the unified controller performs as expected. / Ph. D.

Cost efficient operation and maintenance strategies are crucial for reducing cost of wind energy. Since the regime change from feed-in tariffs to an auction-based bidding system for capacity in most European wind projects, levelized cost of energy is challenged constantly. Therefore, new technologies such as new controllers are developed to improve operation and to increase profit. Previous research studies demonstrated the advantage of increased power output of wake redirection control. However, understanding and quantifying the impact of wind farm control technologies on operation and maintenance strategies is inevitable to evaluate the economic feasibility of such new technologies. Thus, an event-based O&M simulation tool has been developed. Besides general modules, such as the wind turbine model, the weather forecasting model and a model for simulating corrective and planned maintenance, the developed tool also takes wake effects into account. This allows considering different power productions for each individual turbine and a failure rate distribution within the wind farm which is based on altering loads on the different components. Both aspects are driven by changes in operation when applying a new controller technology. Exemplarily, the economic feasibility of a closed-loop active wake steering control has been analysed. Main achievements of this study are the possibility to quantify the impact of the active wake steering control on O&M related KPIs. Results show that additional loads caused by applying yaw-misalignment and redirecting wake, lead to an increase in OPEX. However, the achieved energy production gain and thus related additional revenue exceeds additional cost in the case study. Nonetheless, the study reveals that the profitability of the controller is highly dependent on the electricity price which can be acquired during the wind farm’s lifetime.