No contexto de Smart Grids, determinar a correta localização das fontes causadoras de Variação de Tensão de Curta Duração (VTCD) não é uma tarefa simples, devido à curta duração destes eventos e também, por sua rápida propagação nas redes de distribuição de energia elétrica. Neste sentido, esse trabalho apresentou um método híbrido recursivo baseado em ferramentas da área de aprendizado de máquinas (algoritmo de agrupamento e base de regras), o qual é capaz de localizar as fontes de VTCD, a partir da análise dos das características dos distúrbios disponibilizadas pelos smart meters instalados no sistema. Assim, o trabalho destinouse ao desenvolvimento de uma plataforma em hardware para aquisição, detecção e classificação dos distúrbios, através de um Sistema Operacional de Tempo Real. Em seguida o algoritmo de agrupamento (k-means) agrupou os dados dos medidores de forma a definir dois clusters, onde um deles correspondeu aos medidores que estão longe da região que ocorreu o distúrbio e o outro, correspondeu aos medidores que estavam localizados próximos da região de ocorrência do distúrbio. Na segunda etapa, um sistema baseado em regras determinou qual dos clusters abrangeu o nó de origem. No entanto, quando o algoritmo determinou uma região muito grande, essa região é introduzida recursivamente, como entrada da metodologia desenvolvida, para refinar a região de localização. O sistema resultante foi capaz de estimar a região de localização com uma taxa de acerto acima de 90%. Assim, o método teve sua concepção adequada ao empregado nos centros de controle e operações de concessionárias de energia elétrica, visando apoiar a decisão do corpo técnico para que ações corretivas fossem estabelecidas de forma assertiva. / In the Smart Grids context, the correct location of short-duration voltage variations sources is not a trivial task, because of the short duration of these events and for rapid propagation in the distribution feeder. In this sense, aiming to develop a recursive hybrid method based on machine learning area tools (clustering algorithm and rule base) that is able to locate the sources of short-duration voltage variations, it was used data from smart meters installed along the distribution feeder. The recursive hybrid method, as input, received the disturbance characteristics provided by the meters installed in the system. Thus, this thesis aimed to development of a measurement hardware for signal acquisition, detection, classification through a realtime operating system. Then, k-means clustering algorithm grouped the meters data in order to define two clusters, where one of them corresponded to the meters that were distant from the region that occurred the disturbance and the other one corresponded to the meters, which were located near to the disturbance occurrence region. In a second step, a rule-based system determined which of the clusters corresponded to the source node. When the algorithm determined a very large region, that region was recursively introduced as input of the developed methodology to decrease its size. The resulting system was able to estimate the location region with a accuracy above 90%. Therefore, this method showed a suitable design for employment by operation control centers of power sector concessionaires, aiming to support technical staff decision to stablish assertive corrective actions.

Cette thèse présente un modèle unique du MASG (Modèle d’Architecture du Smart Grid) en considérant l 'état de l’art des différentes directives de recherche du smart grid. Le système hybride de génération d'énergie active marine-hydrogène a été modélisé pour représenter la couche de composants du MASG. Le système intègre l'électrolyseur à membrane d’échange de proton (à l’échelle de méga watt) et les systèmes de piles à combustible en tant que composants principaux du bilan énergétique. La batterie LiFePO4 est utilisée pour couvrir la dynamique rapide de l'énergie électrique. En outre, la thèse analyse le système de gestion de l'énergie centralisé et décentralisé. Le système multi-agents représente le paradigme du système décentralisé. La plate-forme JADE est utilisée pour développer le système multi-agents, en raison de son domaine d'application général, de ses logiciels à licence libre, de son interface avec MATLAB et de sa calculabilité avec les standards de la Fondation des Agents Physiques Intelligentes. Le système de gestion d'énergie basé sur JADE équilibre l'énergie entre la génération (système de conversion d'énergie marine-courant) et la demande (profil de charge résidentielle) pendant les modes de fonctionnement autonome et connecté au réseau. Le modèle proposé du MASG peut être considéré comme une étude de cas pilote qui permet l'analyse détaillée et les applications des différentes directions de recherche du smart grid. / This thesis presents a unique model of the SGAM (Smart Grid Architecture Model) with considering the state of the art of the different research directions of the smart grid and. The hybrid marine-hydrogen active power generation system has been modeled to represent the component layer of the SGAM. The system integrates the MW scale PEM electrolyzer and fuel cell systems as the main energy balance components. The LiFePO4 battery is used to cover the fast dynamics of the electrical energy. Moreover, the thesis analyzes the centralized and the decentralized energy management system. The MAS (Multi-Agent Systems) represents the paradigm of the decentralized system. The JADE platform is used to develop the MAS due to its general domain of application, open source and free license software, interface with MATLAB and the computability with the FIPA (Foundation of Intelligent Physical Agent) standards. The JADE based energy management system balances the energy between the generation (marine-current energy conversion system) and the demand side (residential load profile) during the stand-alone and the grid-connected modes of operation. The proposed model of the SGAM can be considered as a pilot case study that enables the detailed analysis and the applications of the different smart grid research directions.

Regeringen har en vision att till 2050 ska Sverige uppnå en fordonsflotta som är fossilfri och för att uppnå den visionen ska el som drivmedel spela en avgörande roll på marknaden. HEM Nät AB är därmed intresserade av hur deras lokalnät i ett valt område kan påverkas när en större andel av hushållen införskaffar elbilar. Längs områdets högspänningsslinga finns nio nätstationer som matar ut effekt till 815 kunder. En känslighetsanalys genomfördes kring det valda lokalnätet med avseende till dess kapacitet idag till framtida belastningar från elbilar. Analysen baserades på fyra olika nätparametrar som möjligen kan riskeras med avseende till elbilars laddsystem: spänningsfall, transformatorbelastning, övertoner och osymmetri. Olika laddeffekter och kopplingssätt har även jämförts bland nätparametrarna för att visa vilken roll de kan ha i framtiden. Spänningsfallet samt transformatorbelastning för de båda effekterna 3,7 kW och 11 kW uppgick mot de satta nätkraven när 40 % respektive 20 % belastning sker i området. Två vetenskapliga metoder användes för att uppskatta övertonerna där ena tog hänsyn till en reduktion av sammanlagrade övertoner och den andra metoden använde en aritmetisk summering av strömövertonerna. Resultatet visade att med varken en inkluderad reduktion eller med den aritmetiska summeringen kommer övertonerna bli ett problem. Med simuleringen av osymmetri nåddes nätkravet när 7 % mer belastning skedde under en och samma fas. Slutligen kom studien fram till att lokalnätet är relativt starkt och kan klara av 322 elbilar vid 3,7 kW och 161 elbilar vid 11 kW. / The Swedish government have a vision that up untill 2050 Sweden’s transport system is going to be free of fossil fuels and to achieve this vision, electricity is going to be the main fuel and will play a decisive role in the future transportional market. As a result of this, HEM Nät AB is now interested in knowing how their local electrical grid will be affected by a larger amount of electric vehicles, EVs, charged through households. Along the local grid’s high voltage line there are nine substations, which provide power to 815 customers. A sensitivity analysis was conducted on the local grid to appreciate the available capacity for the future load of EVs. The analysis was based on four different gridparameters, which possibly can affect the set conditions of an electrical grid when an EV is being charged: voltage drop, transformer load, harmonics and dissymmetry. Different chargepowers and wirings have also been compared to see what roles they will have in the future. After the simulations and hand calculations all of the gridparameters exceeded the set conditions. This happened at different percentages of the households, which were charging their vehicles. The voltage drop and transformer load for both of the powers, 3,7 kW and 11 kW exceeded the limitations when 40 % respectively 20 % of the studied are was being loaded. Two scientific methods were used to appreciate the added current harmonics, where the first one regarded a reduction of the summarized value of the current harmonics, where the second did not. The results showed, that either of the methods would indicate a problem on the grid. The simulation of the dissymmetry, the limitation was met after 7 % more load was done under one and the same of the phases. Finally, the study concluded that the local grid is relatively strong and can hold 332 EVs with 3,7 kW and 161 EVs with 11 kW.

The Pecan Street Project (PSP) is a public-private initiative that seeks to establish the City of Austin and its electric utility, Austin Energy (AE), as leaders in developing the electric utility system of the future and clean energy economy. The four main components of the project are to: 1) develop a local, public-private consortium dedicated to research and development of clean energy technologies and distributed power generation; 2) open the city’s electric grid to act as a lab to test emerging clean energy technologies; 3) develop a new business model to ensure AE’s continued profitability; and 4) show the world how the new business and systems model can work. This report provides a case study of PSP and describes an analytical approach for evaluating projects, programs, and policies proposed by PSP working groups to develop a cleaner, more efficient electric system. This report includes a history of the project, discusses opportunities and challenges identified by PSP, and evaluates the potential economic, environmental, system, and other impacts of different project ideas through a technical analysis. This report concludes with a series of recommendations to PSP and identifies policy implications for the City of Austin, AE, other policymakers, and other electric utilities. / text

Cette thèse s'inscrit dans le domaine du Smart Grid. Les SGs améliorent la sécurité des réseaux électriques et permettent une utilisation adaptée de l'énergie disponible de manière limitée. Ils augmentent également l'efficacité énergétique globale en réduisant la consommation. L'utilisation de cette technologie est la solution la plus appropriée car elle permet une gestion plus efficace de l'énergie. Dans ce contexte, des compagnies comme Hydro-Québec déploient des réseaux de capteurs pour contrôler les principaux équipements. Pour réduire les coûts de déploiement et la complexité du câblage, un réseau de capteurs semble être une solution optimale. Cependant, son déploiement nécessite une connaissance approfondie de l'environnement. Les postes à haute tension sont des points stratégiques du réseau électrique et génèrent un bruit impulsif qui dégrade les performances des communications sans fil. Les travaux dans cette thèse sont centrés sur le développement de protocoles de communication performants dans ces milieux fortement perturbés. Nous avons proposé une première approche basée sur la concaténation du code à métrique de rang et le code convolutif avec la modulation OFDM. C'est une technique très efficace pour réduire l'effet du bruit impulsif tout en ayant un niveau de complexité assez faible. Une autre solution basée sur un système multi-antennaire est développée. Nous avons aussi proposé un système MIMO coopératif codé en boucle fermée basée sur le code à métrique de rang et le précodeur max-dmin. La deuxième technique est également une solution optimale pour améliorer la fiabilité du système et réduire la consommation énergétique dans les réseaux de capteurs. / This thesis is mainly in the Smart Grid domain. SGs improve the safety of electrical networks and allow a more adapted use of electricity storage, available in a limited way. SGs also increase overall energy efficiency by reducing peak consumption. The use of this technology is the most appropriate solution because it allows more efficient energy management. In this context, manufacturers such as Hydro-Quebec deploy sensor networks in the nerve centers to control major equipment. To reduce deployment costs and cabling complexity, the option of a wireless sensor network seems the most obvious solution. However, deploying a sensor network requires in-depth knowledge of the environment. High voltages substations are strategic points in the power grid and generate impulse noise that can degrade the performance of wireless communications. The works in this thesis are focused on the development of high performance communication protocols for the profoundly disturbed environments. For this purpose, we have proposed an approach based on the concatenation of rank metric and convolutional coding with orthogonal frequency division multiplexing. This technique is very efficient in reducing the bursty nature of impulsive noise while having a quite low level of complexity. Another solution based on a multi-antenna system is also designed. We have proposed a cooperative closed-loop coded MIMO system based on rank metric code and max-dmin precoder. The second technique is also an optimal solution for both improving the reliability of the system and energy saving in wireless sensor networks.

Submitted by SBI Biblioteca Digital (sbi.bibliotecadigital@puc-campinas.edu.br) on 2017-03-23T13:48:47Z No. of bitstreams: 1 IVAN PEDROTTI LEMOS.pdf: 2401459 bytes, checksum: f02681540995cdcf4ae8524cff81fb9c (MD5) / Made available in DSpace on 2017-03-23T13:48:47Z (GMT). No. of bitstreams: 1 IVAN PEDROTTI LEMOS.pdf: 2401459 bytes, checksum: f02681540995cdcf4ae8524cff81fb9c (MD5) Previous issue date: 2017-02-08 / Inteligente. Tarifa Time-of-use tariffs are one way of encouraging consumers to carry out the transfer of load to off-peak intervals, thus making unnecessary new and high investments in generation and transmission and distribution infrastructure. This is therefore a tool for the expansion of energy efficiency, in a new concept of electricity grids, the Smart Grids. However, for this type of charging to be applied, new and modern meters are required, those with the capacity to differentiate consumption hours and that can inform the consumer properly. In this sense, this work is aimed at the development of a meter with an open source platform, in the case Arduino, associated to Analog Devices ADE7753 integrated circuit, transmitting information through IEEE802.11 (Wi-Fi) network, and through an IoT (Internet of Things) platform, to make an assessment whether adoption of the White Tariff is financially beneficial to the consumer in a simple and interactive way. / As tarifas hor?rias s?o uma das formas de incentivar os consumidores a realizarem a transfer?ncia de carga para intervalos fora de ponta, fazendo assim desnecess?rios novos e altos investimentos em gera??o e infraestrutura de transmiss?o e distribui??o. Sendo esta portanto uma ferramenta para a amplia??o da efici?ncia energ?tica, em um novo conceito de redes de energia el?trica, as Smart Grids. Entretanto, para que este tipo de tarifa??o seja aplicado, novos e modernos medidores s?o requeridos, aqueles com capacidade de diferencia??o de hor?rio de consumo e que possam informar devidamente ao consumidor. Neste sentido este trabalho visa o desenvolvimento de um medidor com plataforma open source, no caso o Arduino, associado ao circuito integrado para medi??o de energia el?trica ADE7753 da Analog Devices, transmitindo as informa??es atrav?s de rede IEEE802.11(Wi-Fi), e por meio de uma plataforma para IoT (Internet of Things), realizar uma avalia??o se a ado??o ? Tarifa Branca ? ben?fica financeiramente ao consumidor de forma simples e interativa.

Les réseaux électriques actuels connaîtront un profond changement dans les années à venir. La nouvelle génération est le Smart Grid (SG) ou le réseau électrique intelligent qui se caractérise par une couche d'information et de communication qui permet aux différents composants du réseau de communiquer. Il doit considérer tous les aspects du réseau électrique, le rendant plus intelligent et flexible. Cette notion est présentée comme une réponse à l'évolution du marché de l'électricité, visant à gérer l’augmentation de la demande tout en assurant une meilleure qualité de service et plus de sécurité.Premièrement, nous présentons une formulation de programmation linéaire mixte en entier pour optimiser les systèmes de production et de consommation d'énergie dans une maison intelligente avec un déploiement efficace de plusieurs ressources énergétiques distribuées. Ensuite, à travers la conception d'expériences avec la méthode de Taguchi, divers scénarios sont introduits en faisant varier des facteurs significatifs. Par la suite, une technique heuristique est proposée pour résoudre le problème de la gestion de l'énergie résidentielle en trouvant la solution optimale globale pendant plusieurs jours consécutifs avec une réduction significative du temps d'exécution.Deuxièmement, un modèle de gestion de l'énergie est assuré grâce à des modèles mathématiques pour optimiser l’utilisation du réseau, des ressources énergétiques renouvelables, des véhicules électriques et de la batterie, ainsi que pour différents types d'appareils thermiques et électriques. Une méthode de solution exacte est mise en œuvre pour réduire le coût de l'électricité dans une maison intelligente et pour trouver des modes de fonctionnement de différentes charges. Ensuite, un algorithme d'optimisation math-heuristique est proposé pour résoudre le problème avec un temps de simulation étendu.Enfin, nous étudions le problème de gestion de l'énergie dans un microréseau constitué de plusieurs maisons intelligentes. Chacune d'elles dépose de ressources énergétiques renouvelables, d’un véhicule électrique et d’appareils intelligents. Les ressources d'énergie renouvelable injectent l’excès de l'énergie dans un système de stockage d'énergie partagé. Un modèle mathématique linéaire mixte en entier pour la gestion d'énergie est proposé pour réduire le coût total de fonctionnement du microréseau. Des comparaisons avec des scénarios conventionnels où chaque maison intelligente possède son propre système de stockage d'énergie sont effectuées pour démontrer l’efficacité de la démarche proposée. / The current electricity grids will experience a profound change in the coming years. The new generation is the Smart Grid (SG) which is characterized by information and communication layer enabling the communication between the different components of the grid. It needs to consider all sides of power grid, making it more intelligent and flexible. This notion is presented as an answer to changes in the electricity market, aiming to manage the increased demand while ensuring a better quality of service and more safety.First, we present a mixed integer linear programming formulation to optimize the energy production and consumption systems in a smart home with an effective deployment of several distributed energy resources. Then through the design of experiments with the Taguchi method, diverse scenarios are introduced by varying significant factors. Afterward, a heuristic technique is proposed to solve the problem of residential energy management by finding the global optimum solution for many consecutive days with significant reduction of execution time.Second, an energy management model is proposed thanks to mathematical models to optimize the grid, renewable energy resources, battery and electric vehicles are presented as well as for different type of thermal and electrical appliances. An exact solution method is implemented to reduce the electricity cost in a smart home and find out operation modes of different loads. Then a math-heuristic optimization algorithm is proposed to solve the problem with extended simulation time horizon.Finally, we study a microgrid energy management problem which comprises multiple smart homes. Each of them owns renewable energy resources, one electric vehicle and smart appliances. The renewable energy resources inject the excess energy in the shared energy storage system. An optimized energy management model using mixed integer linear programming is proposed to reduce the total electricity cost in the microgrid. Comparisons with conventional scenarios where each smart home has its individual small energy storage system without sharing energy with their neighbors are done to ensure that the proposed formulation is well efficient.

This thesis focuses on the design and implementation of a software tool able to achieve electricity grid optimal management in a dynamic pricing environment, at the residential level, and from a customer's perspective. The main drivers encouraging a development of energy management at the home level are analyzed, and a system architecture modeling power, thermodynamic and economic subsystems is proposed. The user behavior is also considered. A mathematical formulation of the related energy management optimization problem is proposed based on the linear programming theory. Several cases involving controllable and non-controllable domestic loads as well as renewable energy sources are presented and simulation scenarios illustrate the proposed optimization strategy in each case. The performance of the controller and the changes in energy use are analyzed, and ideas for possible future work are discussed.

Thermal energy storage (TES), the storage of heat or cooling, is a cost-effective energy storage technology that can greatly enhance the performance of the energy systems with which it interacts. TES acts as a buffer between transient supply and demand of energy. In solar thermal systems, TES enables the power output of the plant to be effectively regulated, despite fluctuating solar irradiance. In district energy systems, TES can be used to shift loads, allowing the system to avoid or take advantage of peak energy prices. The benefit of TES, however, can be significantly enhanced by dynamically optimizing the complete energy system. The ability of TES to shift loads gives the system newfound degrees of freedom which can be exploited to yield optimal performance. In the hybrid solar thermal/fossil fuel system explored in this work, the use of TES enables the system to extract nearly 50% more solar energy when the system is optimized. This requires relaxing some constraints, such as fixed temperature and power control, and dynamically optimizing the over a one-day time horizon. In a district cooling system, TES can help equipment to run more efficiently, by shifting cooling loads, not only between chillers, but temporally, allowing the system to take advantage of the most efficient times for running this equipment. This work also highlights the use of TES in a district energy system, where heat, cooling and electrical power are generated from central locations. Shifting the cooling load frees up electrical generation capacity, which is used to sell power to the grid at peak prices. The combination of optimization, TES, and participation in the electricity market yields a 16% cost savings. The problems encountered in this work require modeling a diverse range of systems including the TES, the solar power plant, boilers, gas and steam turbines, heat recovery equipment, chillers, and pumps. These problems also require novel solution methods that are efficient and effective at obtaining workable solutions. A simultaneous solution method is used for optimizing the solar power plant, while a static/dynamic decoupling method is used for the district energy system. / text

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