Examining methods for controlling the electricity demand in Kuwait was the main objective and motivation of this researchp roject. The extensiveu se of air-conditioning for indoor cooling in office and large commercial buildings in Kuwait and the Gulf States represents a major part of the power and electricity consumption in such countries. The rising electricity generation cost and growing rates of consumption continuously demand the construction new power plants. Devising and enforcing Demand-SideM anagemen(t DSM) in the form of energye fficient operations trategies was the response of this research project to provide a means to rectify this situation using the demand-side management technique known as demand levelling or load shifting. State of the art demand-sidem anagementte chniquesh ave been examined through the developmenot f a model basedp redictive control optimisations trategyf or an integrateda ndm odulara pproachto the provisiono f ice thermals torage. To evaluate the potential of ice-storage assisted air-conditioning systems in flattening the demand curve at peak times during the summer months in Kuwait, a model of a Heating, Ventilation, and Air-conditioning (HVAC) plant was developed in Matlab. The model engaged the use of model based predictive control (MPQ as an optimisation tool for the plant as a whole. The model with MPC was developed to chose and decide on which control strategy to operate the integrated ice-storage HVAC plant. The model succeeded in optimising the operation of the plant and introduced encouraging improvement of the performance of the system as a whole. The concept of the modular ice-storage system was introduced through a control zoning strategy based on zonal orientation. It is believed that such strategy could lead to the modularisation of ice-storage systems. Additionally, the model was examined and tested in relation to load flattening and demonstrated promising enhancement in the shape of the load curve and demonstrated flattened demand curves through the employed strategy. When compared with measured data from existing buildings, the model showed potential for the techniques utilised to improve the load factor for office buildings.

Conventionally, to support varying power demand, the utility company must prepare to supply more electricity than actually needed, which causes inefficiency and waste. With the increasing penetration of renewable energy which is intermittent and stochastic, how to balance the power generation and demand becomes even more challenging. Demand response, which reschedules part of the elastic load in users' side, is a promising technology to increase power generation efficiency and reduce costs. However, how to coordinate all the distributed heterogeneous elastic loads efficiently is a major challenge and sparks numerous research efforts. In this thesis, we investigate different methods to provide demand response and improve power grid efficiency. First, we consider how to schedule the charging process of all the Plugged-in Hybrid Electrical Vehicles (PHEVs) so that demand peaks caused by PHEV charging are flattened. Existing solutions are either centralized which may not be scalable, or decentralized based on real-time pricing (RTP) which may not be applicable immediately for many markets. Our proposed PHEV charging approach does not need complicated, centralized control and can be executed online in a distributed manner. In addition, we extend our approach and apply it to the distribution grid to solve the bus congestion and voltage drop problems by controlling the access probability of PHEVs. One of the advantages of our algorithm is that it does not need accurate predictions on base load and future users' behaviors. Furthermore, it is deployable even when the grid size is large. Different from PHEVs, whose future arrivals are hard to predict, there is another category of elastic load, such as Heating Ventilation and Air-Conditioning (HVAC) systems, whose future status can be predicted based on the current status and control actions. How to minimize the power generation cost using this kind of elastic load is also an interesting topic to the power companies. Existing work usually used HVAC to do the load following or load shaping based on given control signals or objectives. However, optimal external control signals may not always be available. Without such control signals, how to make a tradeoff between the fluctuation of non-renewable power generation and the limited demand response potential of the elastic load, and to guarantee user comfort level, is still an open problem. To solve this problem, we first model the temperature evolution process of a room and propose an approach to estimate the key parameters of the model. Then, based on the model predictive control, a centralized and a distributed algorithm are proposed to minimize the fluctuation and maximize the user comfort level. In addition, we propose a dynamic water level adjustment algorithm to make the demand response always available in two directions. Extensive simulations based on practical data sets show that the proposed algorithms can effectively reduce the load fluctuation. Both randomized PHEV charging and HVAC control algorithms discussed above belong to direct or centralized load shaping, which has been heavily investigated. However, it is usually not clear how the users are compensated by providing load shaping services. In the last part of this thesis, we investigate indirect load shaping in a distributed manner. On one hand, we aim to reduce the users' energy cost by investigating how to fully utilize the battery pack and the water tank for the Combined Heat and Power (CHP) systems. We first formulate the queueing models for the CHP systems, and then propose an algorithm based on the Lyapunov optimization technique which does not need any statistical information about the system dynamics. The optimal control actions can be obtained by solving a non-convex optimization problem. We then discuss when it can be converted into a convex optimization problem. On the other hand, based on the users' reaction model, we propose an algorithm, with a time complexity of O(log n), to determine the RTP for the power company to effectively coordinate all the CHP systems and provide distributed load shaping services. / Graduate

La stimulation éléctrique fonctionnelle (SEF) peut améliorer de manière significative la mobilité des blessés médullaires ainsi que la stabilité et la prévention des effets secondaires. Dans le domaine de la SEF pour les membres inférieurs, le couple articulaire doit être fournie de façon appropriée pour effectuer le mouvement prévu afin de maintenir l'équilibre postural. Toutefois, les changements d'état du muscle telle que la fatigue musculaire est une cause majeure qui dégrade ses performances. En outre, la plupart des patients, dont la blessure médulaire est complète, n'ont pas le retour sensorielle qui permet de détecter la fatigue. De plus, et les capteurs de couples in-vivo ne sont pas disponibles à l'heure actuelle. Les systèmes conventionnels de commande SEF sont soit en boucle ouverte ou en boucle fermée mais cependant pas assez robustes aux changements d'état du muscle. L'objectif de cette thèse est le développement de la prédiction du couple articulaire et de la commande en boucle fermée afin d'améliorer les performances de la commande SEF en termes de précision, de robustesse et de sécurité pour les patients. Afin de prédire le couple articliare induit de la SEF, l'électromyographie (EMG) induit est utilisée pour corréler l'activité musculaire éléctrique et mécanique. Bien que la fatigue musculaire représente une variation dans le temps, une dépendance aux sujets et aux protocoles, la méthode proposée d'identification adaptative, basée sur le filtre de Kalman, est capable de prédire le couple articlaire variant dans le temps de manière systématique. La robustesse de la prédiction du couple articulaire a été evaluée lors d'une tâche de suivi de la fatigue en expérimentation chez des sujets blessés médullaires. Les résultats montrent une bonne performance de suivi des variations d'état des muscles en présence de fatigue et face à d'autres perturbations. Basée sur les performances de precision de la méthode prédictive proposée, une nouvelle stratégie de commande utilisant le retour EMG, "EMG-Feedback Predictive Control (EFPC)", est proposée afin de contrôler de manière adaptative les séquences de stimulation en compensant la variation dans le temps de l'état du muscle. De plus, cette stratégie de commande permet explicitement d'éviter d'appliquer une stimulation excessive aux patients, et de générer les séquences de stimulation appropriées pour obtenir la trajectoire désirée des couples articulaires.

This dissertation is dedicated to study the design and utilization of financial contracts and pricing mechanisms for managing the demand/price risks in electricity markets and the price risks in carbon emission markets from different perspectives. We address the issues pertaining to the efficient computational algorithms for pricing complex financial options which include many structured energy financial contracts and the design of economic mechanisms for managing the risks associated with increasing penetration of renewable energy resources and with trading emission allowance permits in the restructured electric power industry. To address the computational challenges arising from pricing exotic energy derivatives designed for various hedging purposes in electricity markets, we develop a generic computational framework based on a fast transform method, which attains asymptotically optimal computational complexity and exponential convergence. For the purpose of absorbing the variability and uncertainties of renewable energy resources in a smart grid, we propose an incentive-based contract design for thermostatically controlled loads (TCLs) to encourage end users' participation as a source of DR. Finally, we propose a market-based approach to mitigate the emission permit price risks faced by generation companies in a cap-and-trade system. Through a stylized economic model, we illustrate that the trading of properly designed financial options on emission permits reduces permit price volatility and the total emission reduction cost.

Atualmente cerca de 15% da população mundial possui algum tipo de deficiência. Para estas pessoas o uso das tecnologias assistivas é essencial. A realidade aumentada surge como uma importante alternativa, para a criação de novas tecnologias assistivas, devido às suas inúmeras formas de rastreamento do participante, que, se combinadas, conseguem proporcionar novas possibilidades de interação. Entretanto, o uso da realidade aumentada, no contexto das tecnologias assistivas, não é uma panaceia, pois cada deficiência é única, assim como cada pessoa possui suas próprias particularidades. Portanto, é importante analisar a acessibilidade destas aplicações, para que o benefício do seu uso possa ser realmente assegurado. Esta dissertação propõe um modelo preditivo de avaliação, baseado no Design Universal e na norma ISO 9241-171. Este modelo é capaz de avaliar a acessibilidade de aplicações de realidade aumentada, quando usadas como tecnologias assistivas. O processo de avaliação consiste no preenchimento de questionários, compostos por questões claras e inteligíveis, para que possam atender à um público multidisciplinar, sem a exigência de qualquer conhecimento prévio em avaliação de acessibilidade. O produto da avaliação feita pelos questionários é um indicador de acessibilidade, que representa o grau de conformidade com os requisitos de acessibilidade. A aplicação dos questionários é sensível ao contexto, cada questionário inclui guias de utilização, que contém os requisitos mínimos do participante, para cada critério de avaliação, desta forma, é possível obter uma visão holística da avaliação, que pode ser customizada para cada participante ou generalizada para uma deficiência específica. O principal objetivo desta dissertação é propor um modelo preditivo, para a avaliação da acessibilidade, servindo aos educadores especiais, desenvolvedores e consumidores de tecnologias assistivas, como critério para a utilização ou não das aplicações de realidade aumentada. / Currently about 15% of the world population has some type of disability. For these people the use of assistive technologies is essential. Augmented reality emerges as an important alternative to the creation of new assistive technologies, due to its numerous forms of participant tracking, which, if combined, can provide new possibilities for interaction. However, the use of augmented reality in the context of assistive technology is not a panacea, as each disability is unique, as well as each person has its own peculiarities. Therefore, it is important to analyze the accessibility of these applications, to ensure the benefit of its use effectively. This work proposes a predictive evaluation model, based on universal design and ISO 9241-171 standard. This model is able to evaluate the accessibility of augmented reality applications, when used as assistive technologies. The evaluation process consists of completing questionnaires, composed of clear and intelligible issues, so that they can meet the multidisciplinary public, without requiring any prior knowledge in evaluating accessibility. The product of evaluation made by questionnaires is a numerical indicator of accessibility, which represents the degree of compliance with accessibility requirements. The questions are sensitives to context, each questionnaire includes guidelines, which contains the minimum requirements of the participant, for each criteria, it is thus possible to obtain a holistic view of the evaluation, which can be customized for each participant or generalized to a specific disability. The main objective of this work is to propose a predictive model for the evaluation of accessibility, serving special educators, developers and assistive technology consumers, as a criteria for the decision of use of augmented reality applications.

Made available in DSpace on 2014-06-11T19:30:51Z (GMT). No. of bitstreams: 0 Previous issue date: 2006-08-30Bitstream added on 2014-06-13T20:47:24Z : No. of bitstreams: 1 ribeiro_jms_me_ilha.pdf: 1485185 bytes, checksum: 5ab0628a95f1aed7502862f70ee550ce (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho apresenta três novas estratégias de controle discreto. O enfoque principal do trabalho foi dado ao Controle Discreto com Modos Deslizantes (CDMD) aplicados em sistemas que possuem atraso no processamento do sinal de controle. As novas estratégias de controle objetivam a elaboração de leis de fácil implementação prática e que ao mesmo tempo sejam robustas a incertezas da planta. Uma característica destas novas abordagens para controle discreto com atraso no tempo é a utilização de um Controle com Modos Deslizantes sem a necessidade de predição do sinal de controle. Os métodos de projeto propostos podem ser aplicados no controle de plantas estáveis ou instáveis com atraso no sinal de controle. Uma das estratégias foi elaborada para realizar controle apenas em sistemas discretos que não possuem atraso no sinal de controle, enquanto que as demais são utilizadas para controle em sistemas com atraso. São apresentadas simulações e resultados de implementações práticas, sobre uma planta estável de Controle Automático da Geração (CAG) e sobre um Sistema Pêndulo Invertido, que caracteriza bem uma planta instável. Os resultados comprovam a eficácia dos novos controladores. / This work presents three new strategies of discrete-time control. The main focus of the work was given to the Sliding Mode Control (SMC) applied in systems that present delay in the processing of the control sign. The new control strategies provide laws of control of easy practical implementation and that at the same time are robust to uncertainties of the plant. A characteristic of these new approaches, for discrete-time control with delay-time, is the use of a Sliding Mode Control without the need of prediction of the control signal. The proposed design methods can be applied in the control of stable or unstable plants, with delay in the control signal. One of the strategies was elaborated to accomplish control just in discrete-time system without delay-time in the control sign, while the others are used for control in systems with delay-time. Simulations and experimental results are shown on a stable plant of Automatic Generation Control (AGC) and on Inverted Pendulum System, that is an unstable plant. The results prove the controllers' effectiveness.

Devant l’augmentation de la part des énergies renouvelables en France, cette thèse propose d’étudier l’augmentation de la flexibilité des réacteurs à eau pressurisée en croisant deux disciplines pour, chacune, atteindre des objectifs complémentaires : l’Ingénierie Système (IS) et l’Automatique.Dans le contexte de l’ingénierie de systèmes complexes et du Model Based Systems Engineering, ce travail propose dans un premier temps une méthode de conception se fondant sur les principes normatifs de l’IS et respectant les habitudes et les pratiques courantes en ingénierie de Framatome. Cette méthode a pour vocation de formaliser et assurer le passage des exigences aux architectures et d’améliorer les capacités de vérification des modèles développés lors de la conception. Elle s’organise autour de langages de modélisation interopérables, couvrant l’ensemble des processus promus par l’IS. La méthode proposée est appliquée sur le système dont les performances sont les plus limitantes dans le contexte de l’augmentation de flexibilité : le Core Control. Ce composant algorithmique du réacteur assure le contrôle des paramètres de fonctionnement du cœur : la température moyenne, la distribution axiale de puissance et la position des groupes de grappes.La thèse propose ensuite des contributions techniques relevant du champ de l’Automatique. Il s’agit de concevoir un système de régulation répondant aux exigences issues de la formalisation IS évoquée ci-dessus. La solution proposée repose sur une stratégie de commande hiérarchisée, utilisant la complémentarité des approches dites de commande multi-objectif, de séquencement de gains et enfin de commande prédictive. Un modèle de réacteur nucléaire simplifié innovant est développé à des fins de conception du système de régulation et de simulations intermédiaires. Les résultats obtenus ont montré les capacités d’adaptation de la démarche proposée à des spécifications diverses. Les performances atteintes sont très encourageantes lorsque évaluées en simulation à partir d’un modèle réaliste et comparées à celles obtenues par les modes de pilotages classiques. / In the event of increasing renewable energies in France, this thesis proposes to study the flexibility increase of pressurized water reactors (PWR) throughout two different engineering disciplines aiming at complementary objectives: Systems Engineering (SE) and Control theory.In a first phase, within the frame of complex systems design and Model Based Systems Engineering, this work proposes a SE method based on SE standard principles and compliant with Framatome’s practices and addressing the revealed issues. This SE contribution is twofold: formalize and ensure the path from requirements to system architectures and enhance the capabilities of models verification. The method revolves around interoperable modeling languages, covering the SE processes: from requirement engineering to system architecture design. The method is applied to the system, which performances are the most limiting in the context of flexibility increase: the Core Control. This algorithmic reactor component ensures the control of: the average coolant temperature, the axial offset and the rod bank position, three of the core main functioning parameters.In order to provide a technical contribution relying on some advanced control methodologies. It consists in designing a control system meeting the requirements defined by the SE method application. The proposed solution is in a two-layer control strategy using the synergies of multi-objective control, gain-scheduling and predictive control strategies. A simplified innovative nuclear reactor model is employed to conceive the control algorithm, simulate and verify the developed models. The results obtained from this original approach showed the ability to adapt to various specifications. Compared to conventional core control modes, the simulation results showed very promising performances, while meeting the requirements, when evaluated on a realistic reactor model.

Face aux forts besoins de réduction de la consommation énergétique et de l’impact environnemental,le bâtiment d’aujourd’hui vise la performance en s’appuyant sur des sourcesd’énergie de plus en plus diversifiées (énergies renouvelables), une enveloppe mieux conçue(isolation) et des systèmes de gestion plus avancés. Plus la conception vise la basse consommation,plus les interactions entre ses composants sont complexes et peu intuitives. Seule unerégulation plus intégrée permettrait de prendre en compte cette complexité et d’optimiser lefonctionnement pour atteindre la basse consommation sans sacrifier le confort.Les techniques de commande prédictive, fondées sur l’utilisation de modèles dynamiqueset de techniques d’optimisation, promettent une réduction des consommations et de l’inconfort.Elles permettent en effet d’anticiper l’évolution des sources et des besoins intermittentstout en tirant parti de l’inertie thermique du bâtiment, de ses systèmes et autres élémentsde stockage. Cependant, dans le cas du bâtiment, l’obtention d’un modèle dynamique suffisammentprécis présente des difficultés du fait d’incertitudes importantes sur les paramètresdu modèle et les sollicitations du système. Les avancées récentes dans le domaine de l’instrumentationdomotique constituent une opportunité prometteuse pour la réduction de cesincertitudes, mais la conception d’un tel système pour une telle application n’est pas triviale.De fait, il devient nécessaire de pouvoir considérer les problématiques de monitoring énergétique,d’instrumentation, de commande prédictive et de modélisation de façon conjointe.Cette thèse vise à identifier les liens entre commande prédictive et instrumentation dansle bâtiment, en proposant puis exploitant une méthode générique de modélisation du bâtiment,de simulation thermique et de résolution de problèmes d’optimisation. Cette méthodologiemet en oeuvre une modélisation thermique multizone du bâtiment, et des algorithmesd’optimisation reposant sur un modèle adjoint et les outils du contrôle optimal. Elle a étéconcrétisée dans un outil de calcul permettant de mettre en place une stratégie de commandeprédictive comportant des phases de commande optimale, d’estimation d’état et decalibration.En premier lieu, nous étudions la formulation et la résolution d’un problème de commandeoptimale. Nous abordons les différences entre un tel contrôle et une stratégie de régulationclassique, entre autres sur la prise en compte d’indices de performance et de contraintes. Nousprésentons ensuite une méthode d’estimation d’état basée sur l’identification de gains thermiquesinternes inconnus. Cette méthode d’estimation est couplée au calcul de commandeoptimale pour former une stratégie de commande prédictive.Les valeurs des paramètres d’un modèle de bâtiment sont souvent très incertaines. Lacalibration paramétrique du modèle est incontournable pour réduire les erreurs de prédictionet garantir la performance d’une commande optimale. Nous appliquons alors notreméthodologie à une technique de calibration basée sur des mesures de températures in situ.Nous ouvrons ensuite sur des méthodes permettant d’orienter le choix des capteurs à utiliser(nombre, positionnement) et des paramètres à calibrer en exploitant les gradients calculéspar la méthode adjointe.La stratégie de commande prédictive a été mise en oeuvre sur un bâtiment expérimentalprès de Chambéry. Dans le cadre de cette étude, l’intégralité du bâtiment a été modélisé,et les différentes étapes de notre commande prédictive ont été ensuite déployées de mainière séquentielle. Cette mise en oeuvre permet d’étudier les enjeux et les difficultés liées àl’implémentation d’une commande prédictive sur un bâtiment réel.Cette thèse est issue d’une collaboration entre le CEA Leti, l’IFSTTAR de Nantes et leG2ELab, et s’inscrit dans le cadre du projet ANR PRECCISION. / More efficient energy management of buildings through the use of Model Predictive Control(MPC) techniques is a key issue to reduce the environmental impact of buildings. Buildingenergy performance is currently improved by using renewable energy sources, a betterdesign of the building envelope (insulation) and the use of advanced management systems.The more the design aims for high performance, the more interactions and coupling effectsbetween the building, its environment and the conditions of use are important and unintuitive.Only a more integrated regulation would take in account this complexity, and couldhelp to optimize the consumption without compromising the comfort.Model Predictive Control techniques, based on the use of dynamic models and optimizationmethods, promise a reduction of consumption and discomfort. They can generate energysavings by anticipating the evolution of renewable sources and intermittent needs, while takingadvantage of the building thermal inertia and other storage items. However, in the caseof buildings, obtaining a good dynamic model is tough, due to important uncertainties onmodel parameters and system solicitations.Recent advances in the field of wireless sensor networks are fostering the deployment ofsensors in buildings, and offer a promising opportunity to reduce these errors. Nevertheless,designing a sensor network dedicated to MPC is not obvious, and energy monitoring,instrumentation, modeling and predictive control matters must be considered jointly.This thesis aims at establishing the links between MPC and instrumentation needs inbuildings. We propose a generic method for building modeling, thermal simulation andoptimization. This methodology involves a multi-zone thermal model of the building, andefficient optimization algorithms using an adjoint model and tools from the optimal controltheory. It was implemented in a specific toolbox to develop a predictive control strategywith optimal control phases, state estimation phases and model calibration.At first, we study the formulation and resolution of an optimal control problem. We discussthe differences between such a control and a conventional regulation strategy, throughperformance indicators. Then, we present a state estimation method based on the identificationof unknown internal gains. This estimation method is subsequently coupled with theoptimal control method to form a predictive control strategy.As the parameters values of a building model are often very uncertain, parametric modelcalibration is essential to reduce prediction errors and to ensure the MPC performance. Consequently,we apply our methodology to a calibration technique based on in situ temperaturemeasurements. We also discuss how our approach can lead to selection techniques in orderto choose calibrated parameters and sensors for MPC purposes.Eventually, the predictive control strategy was implemented on an experimental building,at CEA INES, near Chambéry. The entire building was modeled, and the different steps ofthe control strategy were applied sequentially through an online supervisor. This experimentgave us a useful feedback on our methodology on a real case.This thesis is the result of a collaboration between CEA Leti, IFSTTAR Nantes andG2ELab, and is part of the ANR PRECCISION project.

De nos jours, les systèmes embarqués sont de plus en plus nombreux ce qui impacte fortement les systèmes de conversion de l’énergie. Les contraintes associées se traduisent par une réduction des masses et des pertes afin d’améliorer l’efficacité énergétique de la chaine de conversion. C’est le cas dans le domaine de l’aéronautique où le concept ″d’avion plus électrique″ devient aujourd’hui une réalité. C’est ainsi que la machine synchrone à aimants permanents devient un actionneur d’excellence de par sa puissance massique importante, son faible coût de maintenance et ses qualités dynamiques. Lorsque ces machines sont associées pour remplir des fonctions coopératives (surfaces de vol par exemple) on peut encore réduire la masse embarquée en mutualisant l’électronique de puissance. C’est précisément dans ce cadre que se situe notre travail, en proposant des structures d’alimentation réduites, à base d’électronique de puissance, permettant d’alimenter deux ou plusieurs machines électriques en parallèle et en proposant des lois de commande visant à améliorer le rendement énergétique. Nous nous sommes intéressés plus particulièrement à la Commande Prédictive de deux Machines Synchrones alimentées en parallèle par un Onduleur de Tension Triphasé. Ces machines ont des caractéristiques identiques et doivent suivre un même profil de vitesse avec un couple de charge différent et en tout cas indépendant. L’approche commande prédictive nous conduit à considérer l’onduleur de tension comme un dispositif ayant un nombre fini d’états de commande. Nous devons sélectionner à chaque instant la meilleure solution de commande permettant de minimiser une fonction coût. Cette fonction coût, relative à une ou deux machines, est composée d’une partie représentant la qualité du couple produit (courant IRqR) et d’une autre partie représentant la qualité de la conversion via les pertes produites (courant IRdR). Cette approche opère naturellement à fréquence de découpage variable. Ainsi le document fait état de différentes solutions étudiées montrant les limites d’une telle approche tant sur le plan dynamique que sur le plan des pertes. Pour améliorer cette solution de base nous développons une approche basée sur l’utilisation de vecteurs virtuels. Ces vecteurs virtuels augmentent les possibilités de commande et conduisent à un fonctionnement à fréquence constante au travers d’une modulation de type SVM. La recherche d’un vecteur virtuel optimum est proposée et appliquée sur un dispositif composé de deux machines de faible puissance. Les différentes propositions sont validées par la voie de la simulation numérique et consolidées par des résultats expérimentaux. / Nowadays, embedded systems are more and more numerous that impacted strongly energy conversion systems. Associated constraints translates into a reduction of the masses and the losses to improve energy efficiency in the conversion chain. This is the case in the field of aeronautics or the concept of ″More Electric Aircraft″ now becomes a reality. Therefore, the permanent magnet synchronous machine becomes an actuator of excellence because of its important mass power, its low maintenance cost and its dynamic qualities. When these machines are associated to carry out cooperative functions (for example flight surfaces) can still reduce the mass embedded in pooling power electronics. It is precisely in this context that localizes our work by offering structures power electronics-based, reduced to power for two or more electric machines in parallel and providing control laws aimed at improving energy efficiency. We we are interested specifically in the Predictive Control of two Synchronous Machines connected in parallel with a 3-Phase Converter. These machines have identical characteristics and must follow a same velocity profile with a torque of different load and in any case independent. The predictive control approach leads us to consider the voltage inverter as a device having a finite number of input states and we need to select every moment the best control solution to minimize a cost function. This cost function on one or two machines, is composed of a portion which represents the quality of the produced torque (Iq current) and another party representative quality of the conversion via produced losses (Id current). This approach works naturally for variable switching frequency. Thus the document state of different solutions studied showing the limits of such an approach both dynamic in terms of losses. To improve this basic solution we develop an approach based on the use of virtual vector which increase the possibilities of control and led to operation at constant frequency through a SVM solution. The search for an optimum virtual vector is proposed and applied to a device consisting of two low-power machines. The various proposals are validated through numerical simulation and consolidated by experimental results.

Examining methods for controlling the electricity demand in Kuwait was the main objective and motivation of this researchp roject. The extensiveu se of air-conditioning for indoor cooling in office and large commercial buildings in Kuwait and the Gulf States represents a major part of the power and electricity consumption in such countries. The rising electricity generation cost and growing rates of consumption continuously demand the construction new power plants. Devising and enforcing Demand-SideM anagemen(t DSM) in the form of energye fficient operations trategies was the response of this research project to provide a means to rectify this situation using the demand-side management technique known as demand levelling or load shifting. State of the art demand-sidem anagementte chniquesh ave been examined through the developmenot f a model basedp redictive control optimisations trategyf or an integrateda ndm odulara pproachto the provisiono f ice thermals torage. To evaluate the potential of ice-storage assisted air-conditioning systems in flattening the demand curve at peak times during the summer months in Kuwait, a model of a Heating, Ventilation, and Air-conditioning (HVAC) plant was developed in Matlab. The model engaged the use of model based predictive control (MPQ) as an optimisation tool for the plant as a whole. The model with MPC was developed to chose and decide on which control strategy to operate the integrated ice-storage HVAC plant. The model succeeded in optimising the operation of the plant and introduced encouraging improvement of the performance of the system as a whole. The concept of the modular ice-storage system was introduced through a control zoning strategy based on zonal orientation. It is believed that such strategy could lead to the modularisation of ice-storage systems. Additionally, the model was examined and tested in relation to load flattening and demonstrated promising enhancement in the shape of the load curve and demonstrated flattened demand curves through the employed strategy. When compared with measured data from existing buildings, the model showed potential for the techniques utilised to improve the load factor for office buildings.