Today, there is a growing number of buildings in a neighborhood and business parks that are utilizing renewable energy generation, to reduce their electric bill and carbon footprint. The most current way of implementing a renewable energy generation is to use solar panels or a windmill to generate power; then use a charge controller connected to a battery bank to store power. Once stored, the user can then access a clean source of power from these batteries instead of the main power grid. This type of power structure is utilizing a single module system in respect of one building. As the industry of renewable power generation continues to increase, we start to see a new way of implementing the infrastructure of the power system. Instead of having just individual buildings generating power, storing power, using power, and selling power there is a fifth step that can be added, sharing power. The idea of multiple buildings connected to each other to share power has been named a microgrid by the power community. With this ability to share power in a microgrid system, a catastrophic event which cause shutdowns of power production can be better managed. This paper then discusses the data from simulations and a built physical model of a resilient microgrid utilizing these principles.

Cette thèse s’intéresse à la gestion décentralisée à l’aide des systèmes multi-agents de l’énergie, notamment de sources renouvelables, dans le contexte des réseaux électriques intelligents (smart grids). Nos travaux de recherche visent à minimiser la facture énergétique des consommateurs en se focalisant sur deux verrous essentiels que nous nous proposons de lever : (1) résoudre le problème de l’intermittence des énergies renouvelables; (2) minimiser les pertes d’énergie. Pour pallier le problème d’intermittence des énergies renouvelables et dans le but de maintenir un coût énergétique peu onéreux même lors des pics d’utilisation, nous avons intégré un système de stockage intelligent. Nous avons, en effet, proposé des algorithmes permettant d’utiliser les systèmes de stockage intelligents et la négociation multi-agents pour réduire la facture énergétique tout en conservant un taux de décharge minimal de la batterie et une perte énergétique minimale. La validation par simulation de nos contributions a montré que celles-ci répondent aux enjeux identifiés, notamment en réduisant le coût de l’énergie pour les consommateurs en comparaison aux travaux de l’état de l’art. / This thesis focuses on the decentralized management using multi-agent systems of energy, including renewable energy sources, in the smart grid context. Our research aims to minimize consumers’ energy bills by answering two key challenges: (1) handle the problem of intermittency of renewable energy sources; (2) reduce energy losses. To overcome the problem of renewable resources intermittency and in order to minimize energy costs even during peak hours, we integrated an intelligent storage system. To this end, we propose many algorithms in order to use intelligent storage systems and multi-agent negotiation algorithm to reduce energy cost while maintaining a minimal discharge rate of the battery and minimal energy loss. The validation of our contributions has shown that our proposals respond to the identified challenges, including reducing the cost of energy for consumers, in comparison to the state of the art.

Modern power generation aims to utilize renewable energy sources such as solar power and wind to supply customers with power. This approach avoids exhaustion of fossil fuels as well as provides clean energy. Microgrids have become popular over the years, as they contain multiple renewable power sources and battery storage systems to supply power to the entities within the network. These microgrids can share power with the main grid or operate islanded from the grid. During an islanded scenario, self-sustainability is crucial to ensure balance between supply and demand within the microgrid. This can be accomplished by a smart microgrid that can monitor system conditions and respond to power imbalance by shedding loads based on priority. Such a method ensures security of the most important loads in the system and manages energy by automatically disconnecting lower priority loads until system conditions have improved. This thesis introduces a prioritized load shedding algorithm for the microgrid at the University of North Texas Discovery Park and highlight how such an energy management algorithm can add reliability to an islanded microgrid.

Indiana University-Purdue University Indianapolis (IUPUI) / With the rapid growth of technology, scientists are trying to find ways to make the world a more efficient and eco-friendly place. The research and development of electric vehicles suddenly boomed since natural resource are becoming very scarce. The significance of an electric vehicle goes beyond using free energy, it is environ- mental friendly. The objective of this thesis is to understand what Vehicle to Grid Communication (V2G) for an electric vehicle is, and to implement a model of this highly efficient system into a Hybrid Petri Net. This thesis proposes a Hybrid Petri net modeling of Vehicle to Grid (V2G) Communication topology. Initially, discrete, continuous, and hybrid Petri net's are defined, familiarized, and exemplified. Secondly, the Vehicle and Grid side of the V2G communication system is introduced in detail. The modeling of individual Petri nets, as well as their combination is discussed thoroughly. Thirdly, in order to prove these systems, simulation and programming is used to validate the theoretical studies. A Matlab embedded simulation program known as SimHPN is used to simulate specific scenario's in the system, which uses Depth-first Search (DFS) Algorithm. In addition to SimHPN simulation program, Matlab program is made to output four levels of the reachability tree as well as specifying duplicate and terminate nodes. This code incorporates a technique known as Breadth-first Search (BFS) Algorithm.

Neste trabalho é apresentada uma abordagem de controle de demanda para consumidores residenciais de baixa tensão, visando melhoria da eficiência energética em Smart Grids. Inicialmente, um emulador de cargas elétricas residenciais é modelado com base na literatura. O emulador é composto pelo modelo de um reservatório de aquecimento de água (boiler), o modelo de um aparelho de ar condicionado e também modelos de consumo de iluminação, televisores e uma geladeira. Utilizando o software Matlab foi realizada a implementação e simulação do emulador. Os principais algoritmos de controle de demanda são investigados, a fim de verificar o seu desempenho quando aplicados ao conjunto de cargas residenciais. Esses algoritmos normalmente realizam o controle de demanda a partir de um sistema de prioridades. Ainda, a partir dessa analise demostra-se que estes algoritmos consideram níveis de conforto do usuário, porém não permitem o acionamento de duas ou mais cargas em um mesmo período caso a demanda da residência ultrapasse um limite predeterminado. Portanto, propõem-se um algoritmo de controle de demanda adaptativo que utiliza o método de busca Rosenbrock, com o objetivo de sobrepujar tais limitações. O procedimento proposto realiza a operação das cargas residenciais de forma gradual considerando níveis de prioridade e parâmetros de conforto dos usuários. Demonstra-se através de simulações e experimentos que através do método proposto é possível realizar a ativação de diversas cargas concorrentemente, desde que respeitados os níveis de conforto e de demanda. Para obtenção dos resultados experimentais o controlador de demanda foi implementado em um sistema embarcado e testado com o emulador de cargas elétricas residenciais implementado em uma arquitetura HIL (Hardware-in-the-loop). Analisando os resultados, observou-se que o consumo de energia foi o mesmo para todos os cenários simulados sendo que a demanda se manteve abaixo dos limites parametrizados. Porém com o limitador de demanda ativo, se obteve uma redução de até 52% no tempo de aquecimento da água utilizando o controlador de demanda adaptativo, dessa forma o desconforto dos usuários pode ser minimizado. / This work presents an approach to control demand for residential low voltage consumers, aiming to improve energy efficiency in Smart Grids. Initially, an emulator of residential electric loads is modeled based on the literature. The emulator consists of a reservoir for water heating model, the model of an air conditioner and also models of consumption for lighting, televisions and a refrigerator. The implementation and simulation were performed using software Matlab. The demand control algorithms are investigated in order to verify its performance when applied to the set of residential loads. These algorithms typically perform control demand from a system of priorities. Still, from this analysis it demonstrates that these algorithms consider levels of user comfort, but do not allow the drive of two or more loads in the same period of residence if the demand exceeds the limit. Therefore, we propose a control algorithm that uses Rosenbrock search of demand adaptive method, aiming to overcome these limitations. The proposed procedure performs the operation of residential loads gradually considering priority levels and parameters of comfort of users. It is shown through simulations and experiments using the proposed method can perform the activation of several concurrently loads, provided they comply with the limits of comfort and demand. To obtain the experimental results demand the controller was implemented in an embedded system and tested with the emulator residential electrical loads implemented in a HIL (Hardware-in-theloop) architecture. Analyzing the results, it was observed that the power consumption is the same for all scenarios simulated and demand remained below parametric limits. But with the demand limiter active, we obtained a reduction of up to 52% in heat water using the demand controller adaptive, so the discomfort of the users can be minimized.

Finep; CAPES; CNPq; FA; ANEEL; ENGIE; / Esta tese apresenta aplicações de redes de Bragg em fibra óptica (FBG) para medição de parâmetros em máquinas elétricas. Os resultados apresentados permitem explorar novas técnicas de instrumentação que mostram o potencial de utilização de FBGs em ambientes industriais, como a medição de temperatura em uma usina hidrelétrica, e de investigação em laboratório, como no estudo da deformação dinâmica do estator de motores de indução. As técnicas de instrumentação apresentadas podem ser utilizadas isoladamente ou integradas, de forma a obter uma instrumentação multiparamétrica em usinas hidrelétricas ou em ambientes industriais que utilizam motores de indução em seu processo produtivo. A tese é organizada em forma de coletânea de artigos científicos, os quais apresentam a medição de temperatura e determinação de um modelo térmico de uma ponte retificadora utilizada para ajustar a corrente de campo do rotor de um gerador, um sensor de campo magnético, medição da deformação dinâmica do estator de motores de indução e caracterização de um acelerômetro óptico biaxial. Os resultados para medição de temperatura nos tiristores utilizados na ponte retificadora mostram a dependência entre temperatura e corrente de excitação, onde oscilações de corrente levam a oscilações de temperatura. O ajuste a partir do modelo térmico desenvolvido para o sistema apresenta um erro de 1,5oC em comparação com as medidas pelas FBGs. O sensor de campo é baseado na magnetostricção, sendo utilizadas duas FBGs. Uma delas para medição de deformação e outra para compensação de temperatura. No sensor de campo é apresentada a variação da resposta em função da temperatura, onde a magnetoestricção apresenta comportamento não-linear e sua saturação também varia em função temperatura. A medida de deformação do estator empregando as FBGs apresenta uma boa relação sinal ruído, com 80 dB para a harmônica fundamental, e as frequências observadas na vibração são as esperadas teoricamente. Além disso, com a utilização de duas FBGs pode-se observar a natureza girante da força magnética do entreferro. A medição de deformação do estator trata-se de uma técnica de análise inovadora, sendo a principal contribuição desta tese. Os resultados obtidos com a medida de deformação do estator são utilizados para validar as medidas de vibração de um acelerômetro óptico biaxial utilizado em um motor de indução. O acelerômetro óptico biaxial é insensível à variação de temperatura, podendo ser aplicado para medição de vibração em máquinas elétricas. / This paper presents the application of fiber Bragg gratings (FBG) for parameters measurement in electrical machines. The results allow to explore new instrumentation techniques and show the potential for industrial applications, presenting the measurement in an hydroelectric power plant, and laboratory research, such as the dynamic stator strain measurement. Each instrumentation technics presented in this paper has a potential to use isolated or integrated in order to obtain a multiparameter instrumentation in hydroelectric power plants or industrial environments that using induction motors in its production process. This paper is organized in a collection of articles, and the FBG applications are the temperature measurement and simulation of a rectifier bridge used to adjust the rotor field current of a power generator, a magnetic field sensor, , a biaxial optical accelerometer and the measurement of the stator dynamic strain of an induction motor. The results for the thyristor temperature measurement show the dependence of temperature and excitation current, where current oscillations lead to temperature fluctuations. The simulation of the thermal model presents a 1.5oC error compared to measures by the FBGs. The field sensor is based on magnetostriction, property where the magnetic material undergo deformation in the presence of a magnetic field. For this sensor are used two FBGs for temperature measurement and deformation in Terfenol-D, material with magnetostrictive properties. In the magnetic field sensor the response is a function of temperature, where the magnetostriction and saturation presents non-linear behavior varies as a function of temperature. Stator strain measurement using the FBGs has a good relationship signal noise, 80 dB for the fundamental harmonic and the observed frequencies in the vibration are theoretically expected. Moreover, with the use of two sensors can be determine the rotating nature of the air gap magnetic force. Finally, the biaxial optical accelerometer does not have is insensitive to temperature variations and can be applied for measuring vibration in electrical machines.

Neste trabalho é apresentada uma abordagem de controle de demanda para consumidores residenciais de baixa tensão, visando melhoria da eficiência energética em Smart Grids. Inicialmente, um emulador de cargas elétricas residenciais é modelado com base na literatura. O emulador é composto pelo modelo de um reservatório de aquecimento de água (boiler), o modelo de um aparelho de ar condicionado e também modelos de consumo de iluminação, televisores e uma geladeira. Utilizando o software Matlab foi realizada a implementação e simulação do emulador. Os principais algoritmos de controle de demanda são investigados, a fim de verificar o seu desempenho quando aplicados ao conjunto de cargas residenciais. Esses algoritmos normalmente realizam o controle de demanda a partir de um sistema de prioridades. Ainda, a partir dessa analise demostra-se que estes algoritmos consideram níveis de conforto do usuário, porém não permitem o acionamento de duas ou mais cargas em um mesmo período caso a demanda da residência ultrapasse um limite predeterminado. Portanto, propõem-se um algoritmo de controle de demanda adaptativo que utiliza o método de busca Rosenbrock, com o objetivo de sobrepujar tais limitações. O procedimento proposto realiza a operação das cargas residenciais de forma gradual considerando níveis de prioridade e parâmetros de conforto dos usuários. Demonstra-se através de simulações e experimentos que através do método proposto é possível realizar a ativação de diversas cargas concorrentemente, desde que respeitados os níveis de conforto e de demanda. Para obtenção dos resultados experimentais o controlador de demanda foi implementado em um sistema embarcado e testado com o emulador de cargas elétricas residenciais implementado em uma arquitetura HIL (Hardware-in-the-loop). Analisando os resultados, observou-se que o consumo de energia foi o mesmo para todos os cenários simulados sendo que a demanda se manteve abaixo dos limites parametrizados. Porém com o limitador de demanda ativo, se obteve uma redução de até 52% no tempo de aquecimento da água utilizando o controlador de demanda adaptativo, dessa forma o desconforto dos usuários pode ser minimizado. / This work presents an approach to control demand for residential low voltage consumers, aiming to improve energy efficiency in Smart Grids. Initially, an emulator of residential electric loads is modeled based on the literature. The emulator consists of a reservoir for water heating model, the model of an air conditioner and also models of consumption for lighting, televisions and a refrigerator. The implementation and simulation were performed using software Matlab. The demand control algorithms are investigated in order to verify its performance when applied to the set of residential loads. These algorithms typically perform control demand from a system of priorities. Still, from this analysis it demonstrates that these algorithms consider levels of user comfort, but do not allow the drive of two or more loads in the same period of residence if the demand exceeds the limit. Therefore, we propose a control algorithm that uses Rosenbrock search of demand adaptive method, aiming to overcome these limitations. The proposed procedure performs the operation of residential loads gradually considering priority levels and parameters of comfort of users. It is shown through simulations and experiments using the proposed method can perform the activation of several concurrently loads, provided they comply with the limits of comfort and demand. To obtain the experimental results demand the controller was implemented in an embedded system and tested with the emulator residential electrical loads implemented in a HIL (Hardware-in-theloop) architecture. Analyzing the results, it was observed that the power consumption is the same for all scenarios simulated and demand remained below parametric limits. But with the demand limiter active, we obtained a reduction of up to 52% in heat water using the demand controller adaptive, so the discomfort of the users can be minimized.

Indiana University-Purdue University Indianapolis (IUPUI) / Reliability of the wide-area power system is becoming a greater concern as the power grid is growing. Delivering electric power from the most economical source through fewest and shortest transmission lines to customers frequently increases the stress on the system and prevents it from maintaining its stability. Events like loss of transmission equipment and phase to ground faults can force the system to cross its stability limits by causing the generators to lose their synchronism. Therefore, a helpful solution is detection of these dynamic events and prediction of instability. Decision Trees (DTs) were used as a pattern recognition tool in this thesis. Based on training data, DT generated rules for detecting event, predicting loss of synchronism, and selecting stabilizing control. To evaluate the accuracy of these rules, they were applied to testing data sets. To train DTs of this thesis, direct system measurements like generator rotor angles and bus voltage angles as well as calculated indices such as the rate of change of bus angles, the Integral Square Bus Angle (ISBA) and the gradient of ISBA were used. The initial method of this thesis included a response based DT only for instability prediction. In this method, time and location of the events were unknown and the one shot control was applied when the instability was predicted. The control applied was in the form of fast power changes on four different buses. Further, an event detection DT was combined with the instability prediction such that the data samples of each case was checked with event detection DT rules. In cases that an event was detected, control was applied upon prediction of instability. Later in the research, it was investigated that different control cases could behave differently in terms of the number of cases they stabilize. Therefore, a third DT was trained to select between two different control cases to improve the effectiveness of the methodology. It was learned through internship at Midwest Independent Transmission Operators (MISO) that post-event steady-state analysis is necessary for better understanding the effect of the faults on the power system. Hence, this study was included in this research.

Redes inteligentes de distribuição de energia fornecem serviços com o potencial de aumentar a eficiência energética e a qualidade de vida da sociedade, mas possuem requisitos severos de tempo de resposta, confiabilidade, escalabilidade e QoS. As chaves ópticas são dispositivos comutadores de caminhos em fibras ópticas popularmente utilizados para trocas físicas de rotas. Neste trabalho sugere-se utilizar estes dispositivos para ativamente reorganizar uma rede com o objetivo de diminuir a latência de comunicação, visando atender aos requisitos de comunicações dos serviços de redes inteligentes. Foram estudadas as características de protocolos de roteamento conhecidos e aplicou-se o algoritmo de Dijkstra na criação de quatro heurísticas de otimização dos caminhos máximos em redes com chaves ópticas. Simulações realizadas mostram que as heurísticas propostas reduzem o número de saltos nos caminhos máximos, levando à redução de latência. É sugerida a continuação deste estudo aperfeiçoando as heurísticas propostas com outros mecanismos de otimização e diferentes métricas, como redução de congestionamento de tráfego e de consumo de energia na rede. / Smart grid networks provide services with the potential to increase energy efficiency and the quality of life of society, but have strict requirements regarding response time, reliability, scalability and QoS. The optical switches are fiber optic switching devices commonly used for physical route changing. In this study, it is suggested to use these devices to actively rearrange a network in order to reduce the communication latency, to meet the communications requirements of smart grid services. The characteristics of known routing protocols have been studied and the Dijkstra algorithm has been applied at the creation of four heuristics that aim to optimize the maximum paths in networks with optical switches. The simulations show that the heuristics reduce the maximum number of hops in the paths, leading to reductions in latency. It is suggested the continuation of this study improving the heuristics with other optimization engines and different metrics, such as reducing traffic congestion and energy.

Redes inteligentes de distribuição de energia fornecem serviços com o potencial de aumentar a eficiência energética e a qualidade de vida da sociedade, mas possuem requisitos severos de tempo de resposta, confiabilidade, escalabilidade e QoS. As chaves ópticas são dispositivos comutadores de caminhos em fibras ópticas popularmente utilizados para trocas físicas de rotas. Neste trabalho sugere-se utilizar estes dispositivos para ativamente reorganizar uma rede com o objetivo de diminuir a latência de comunicação, visando atender aos requisitos de comunicações dos serviços de redes inteligentes. Foram estudadas as características de protocolos de roteamento conhecidos e aplicou-se o algoritmo de Dijkstra na criação de quatro heurísticas de otimização dos caminhos máximos em redes com chaves ópticas. Simulações realizadas mostram que as heurísticas propostas reduzem o número de saltos nos caminhos máximos, levando à redução de latência. É sugerida a continuação deste estudo aperfeiçoando as heurísticas propostas com outros mecanismos de otimização e diferentes métricas, como redução de congestionamento de tráfego e de consumo de energia na rede. / Smart grid networks provide services with the potential to increase energy efficiency and the quality of life of society, but have strict requirements regarding response time, reliability, scalability and QoS. The optical switches are fiber optic switching devices commonly used for physical route changing. In this study, it is suggested to use these devices to actively rearrange a network in order to reduce the communication latency, to meet the communications requirements of smart grid services. The characteristics of known routing protocols have been studied and the Dijkstra algorithm has been applied at the creation of four heuristics that aim to optimize the maximum paths in networks with optical switches. The simulations show that the heuristics reduce the maximum number of hops in the paths, leading to reductions in latency. It is suggested the continuation of this study improving the heuristics with other optimization engines and different metrics, such as reducing traffic congestion and energy.