Operation and restoration of bulk power systems using distributed energy resources and multi-microgrids

The fast-paced and meaningful penetration of distributed energy resources (DERs), such as variable renewable energy sources (RESs), concurrently with the widespread occurrence of natural disasters and man-made threats, has raised several challenges for the modern bulk power systems (BPSs) status quo. Although the DERs are demanding new solutions to ensure adequate stability and security levels, these resources enable significant opportunities to improve multiple BPS perspectives. In this view, seeking to capitalize on these novel features, while aware of the significant changes to BPS outlook, this thesis is focused on developing new methods able to capitalize on modern monitoring infrastructures, DERs and control areas opportunities toward the improvement of BPS operation and stability. Specifically, the thesis focuses on: 1) First, a novel method for the improvement of the static security region (SSR) is proposed based on a new network partitioning algorithm. The proposed algorithm focuses on modern BPS with high penetration of variable RES generation. It divides the BPS into coherence areas according to its criticality mapping, and consequently, areas are adaptively associated with SSRs generators groups. To this end, each bus is assigned a criticality index from the potential energy function, whereas this calculation is based on the data of the wide-area measurement system (WAMS) using phasor measurement unit (PMU); 2) Second, a novel area-based sensitivity index for voltage stability support is proposed, exploring both the network-wide sensitivity and the local characteristics of voltage collapse. The developed index focuses on the determination of the most effective buses for voltage support and their respective capability of increasing the system’s load margin. For this, a novel area-based outlook is developed taking advantage of the new possibilities enabled by BPS distributed controllable resources, such as flexible resources (FRs)

Communication technology selection method for smart energy metering based on analytic hierarchy process

As new communication technologies continue to emerge and the integration of these technologies into the modernization of the electricity grid becomes increasingly necessary, a variety of communication protocols and combinations are being explored for their potential use in the smart grid domain. However, given the multitude of technological possibilities available, choosing the optimal technology capable of adequately addressing the communication requirements of the intelligent grid remains a challenge for utilities. This is due, on the one hand, to the fact that different intelligent grid applications have different qualitative and quantitative communication requirements. Moreover, on the other hand, each technology has advantages and disadvantages concerning its performance characteristics in such requirements. This work uses the AHP (Analytic Hierarchy Process) methodology to select the wireless technology that presents the best performance characteristics concerning determined requirements. For this, a computational algorithm was developed in the Matlab programming environment, through which criteria such as data rate, latency, range, security, reliability, and interoperability were compared to select the best technological alternative among Wi-Fi, ZigBee, Z-Wave, and Bluetooth. Data collected from the literature review, with the performance characteristics of these technologies, were applied in a single case study simulating the practical implementation of this work. Among the analyzed criteria, simulations demonstrated that Wi-Fi was the winning technology alternative with 32.353%, followed by Z-Wave with 29.865% in second place, and ZigBee and Bluetooth were ranked third and fourth with 25.255% and 12.527%, respectively. In addition, sensitivity analysis shows how the AHP methodology can be a feasible alternative to assist decision-making in the smart grid domain.À medida que novas tecnologias de comunicação continuam a surgir e a integração destas tecnologias na modernização da rede elétrica se torna cada vez mais necessária, uma variedade de protocolos e combinações de tecnologias de comunicação vem sendo explorados para a sua potencial utilização no domínio da rede inteligente. No entanto, dada a multiplicidade de possibilidades tecnológicas disponíveis, a escolha da melhor tecnologia capaz de responder, adequadamente, aos requisitos de comunicação da rede elétrica inteligente continua sendo um desafio para diferentes atores interessados. Isto se deve, por um lado, ao fato de diferentes aplicações de rede inteligente terem diferentes requisitos de comunicação, quer sejam quantitativos ou qualitativos. Além disso, por outro lado, cada tecnologia tem vantagens e desvantagens relacionadas com as suas características de desempenho em tais requisitos. Este trabalho, portanto, utiliza a metodologia AHP (Analytic Hierarchy Process) para selecionar a tecnologia sem fios que apresenta as melhores características de desempenho relativamente a determinados requisitos. Para tal, foi desenvolvido um algoritmo computacional no ambiente de programação Matlab, através do qual critérios tais como taxa de dados, latência, alcance, segurança, confiabilidade e interoperabilidade foram comparados para selecionar a melhor alternativa tecnológica entre Wi-Fi, ZigBee, Z-Wave e Bluetooth. Os dados coletados na revisão de literatura, com as características de desempenho destas tecnologias, foram aplicados num único estudo de caso simulando a implementação prática deste método em ambiente residencial. Dentre os critérios analisados, as simulações demonstraram que o Wi-Fi foi a alternativa tecnológica vencedora com 32,353%, seguido pelo Z-Wave com 29,865% em segundo lugar, e ZigBee e Bluetooth ficaram em terceiro e quarto lugar com 25,255% e 12,527%, respectivamente. Além disso, a análise de sensibilidade, dos resultados, mostra como a metodologia AHP pode ser uma alternativa viável para auxiliar na tomada de decisões no domínio da rede inteligente

The use of advanced signal processing and deep learning for pattern recognition in integrated metrics of quality performance: a smart grid application

Power quality (PQ) is not a new theme, but it should not be neglected in any way, as its performance parameters will reveal problems in the adequacy between the consumer equipment and the electrical grid. With the ongoing transformations in electrical power systems, characterized by the high penetration of renewable energy sources, the massive insertion of components based on power electronics in the network, and the decentralization of generation, these issues are becoming increasingly important. In Smart Grids, solutions are sought for more advanced solutions to solve PQ disturbances problems. Advanced signal processing plays an essential role in dealing with the network and supporting various applications within this context and Artificial Intelligence (AI), which has gained significant prominence to feed applications with innovative solutions in several areas. This research investigates the use of advanced signal processing and Deep Learning techniques for pattern recognition and classification of signals with PQ disorders. For this purpose, the Continuous Wavelet Transform with a filter bank is used to generate 2-D images with the time-frequency representation from signals with voltage disturbances. The work aims to use Convolutional Neural Networks (CNN) to classify this data according to the images’ distortion. In this implementation of AI, specific stages of design, training, validation, and testing were carried out for a model elaborated by the case file and a knowledge transfer technique with the pre-trained networks SqueezeNet, GoogleNet, and ResNet-50. The work was developed in the MATLAB/Simulink software, all signal processing stages, CNN design, simulation, and the investigated data generation. All steps have their objectives fulfilled, culminating in the excellent execution and development of the research. The results sought high precision for CNN de Scratch and ResNet-50 in classify the test set. The other two models obtained not-so-high accuracy, and the results are consistent when compared with different methodologies. Considerations about the results were pointed out. Finally, some conclusions were established and a philosophical reflection on the role of AI and advanced signal processing in electrical power systems.Agência 1Qualidade de Energia não é uma temática nova, porém de forma alguma deve ser negligenciada, pois seus parâmetros de performance indicam problemas na adequação entre o equipamento do consumidor e a rede elétrica. Com as transformações em andamento nos sistemas elétricos de potência, caracterizados pela alta penetração de fontes renováveis de energia, inserção massiva de componentes baseados em eletrônica de potência na rede e descentralização da geração, essas questões se tornam cada vez mais importantes. Nas Redes Inteligentes, busca-se soluções cada vez mais avançadas para solucionar questões dos distúrbios da Qualidade de Energia. Dentro desse contexto, o processamento avançado de sinais possui um papel importante para tratar as medições da rede e apoiar diversas aplicações. A Inteligência Artificial, tem ganhado grande destaque dar suporte para aplicações com soluções inovadoras em diversas áreas. Esta pesquisa tem como objetivo investigar o uso de processamento avançado de sinais e técnicas de Aprendizagem Profundo ("Deep Learning") para reconhecimento de padrões e classificação de sinais com distúrbios da Qualidade de Energia. Para este propósito, a Transformada Wavelet Contínua com um banco de filtros é usada para gerar imagens 2-D no domínio do tempo-frequência a partir de sinais com distúrbios de tensão. O trabalho visa utilizar Redes Neurais Convolucionais para classificar essas imagens de acordo com a respectiva distorção. Nesta implementação de Inteligência Artificial, etapas específicas de projeto, treinamento, validação e teste serão realizadas para um modelo elaborado pelo autor e também utilizando a técnica de transferência de conhecimento com as redes pré-treinadas SqueezeNet, GoogleNet, e ResNet-50. O trabalho foi desenvolvido no software MATLAB/Simulink, todas as etapas de processamento do sinal, projeto de modelos de classificação, simulação e geração dos dados investigados. Todas as etapas tiveram seus objetivos específicos cumpridos, culminando na boa execução e desenvolvimento da pesquisa. Os resultados obtidos mostraram alta precisão para "CNN de Scratch" e ResNet-50 em classificar o conjunto de testes. Os outros dois modelos obtiveram acurácias não tão altas, e os resultados se mostram consistentes ao comparar com outras metodologias. Considerações sobre os resultados foram apontadas. Por fim, algumas conclusões foram estabelecidas, assim como uma reflexão filosófica sobre o papel dos tópicos abordados para os sistemas elétricos de potência

Validation of seasonal climate predictions for south america: ecmwf-seas5 global model

This work evaluated the quality of ECMWF-SEAS5 seasonal precipitation and 2 m temperature predictions for South America. For this purpose, datasets of hindcasts from 1993 to 2016 and forecasts from 2017 to 2020 were used. The predictions were validated against CPC precipitation and temperature analyses. The average seasonal fields indicated that the model has a good representation of the seasonal rainfall patterns in South America, adequately simulating the wet and dry phases of the monsoon. However, the hindcasts present systematic overestimation of rain in the Amazon, South Brazil, Southeast Brazil, and northern South America sectors. In addition, the model also presents an underestimation of rain in Northeast Brazil and southeastern South America. Regarding the temperature results, the model showed a systematic cold bias over most of the continent, except for portions of Northeast Brazil and southeastern South America. The skill score evaluation showed that the main correlations of precipitation and temperature anomaly occur in regions of high climate predictability, such as the tropical latitudes of the continent. The regionalized mean anomalies indicated that ECMWF-SEAS5 has a good performance to simulate the interannual variability of rainfall and temperature, especially in transition seasons. However, hindcasts were not efficient for predicting anomalous events such as the 2014/2015 drought in Southeast Brazil and the 2015 drought in the east of the Amazon. The analysis of the forecasts from 2017 to 2020 showed that systematic errors of overestimation (underestimation) of rainfall persist in regions such as the Amazon, Southeast Brazil, South Brazil, and northern South America (Northeast Brazil and southeastern South America). Similarly, temperature underestimation (overestimation) errors in most of the continent (Northeast Brazil and southeastern South America) remain in the real-time forecasts. Overall, it is concluded that the ECMWF-SEAS5 model performs seasonal rainfall and temperature predictions for South America with considerable dexterity and potential for diverse applications. However, its limitations and errors must be considered for the best use of its predictions.Este trabalho avaliou a qualidade das previsões climáticas sazonais de precipitação e temperatura do ar do ECMWF-SEAS5 para a América do Sul. Para isso, foram utilizados conjuntos de dados de hindcasts de 1993 a 2016 e de forecasts de 2017 a 2020. As previsões foram validadas mediante comparação com análises de precipitação e temperatura do CPC. Os campos sazonais médios indicaram que o modelo possui boa representação dos padrões sazonais de chuva na América do Sul, simulando adequadamente a fase úmida e seca da monção. Apesar disso, os hindcasts apresentam superestimativa sistemática de chuva em setores como a Amazônia, Sul e Sudeste brasileiros e norte da América do Sul. Além disso, o modelo também apresenta subestimativa de chuva no Nordeste do Brasil e sudeste da América do Sul. Para a temperatura, o modelo apresentou viés frio sistemático sobre a maior parte do continente, com exceção de porções do Nordeste do Brasil e sudeste da América do Sul. A avaliação da performance do modelo mostrou que as principais correlações de anomalia de precipitação e temperatura ocorrem em regiões de alta previsibilidade climática como as latitudes tropicais do continente. As anomalias médias regionalizadas indicam que o modelo possui boa capacidade de simular a variabilidade interanual de chuva e temperatura, principalmente em estações de transição. Entretanto, os hindcasts não se mostraram eficientes para a previsão de eventos anômalos como a seca de 2014/2015 no Sudeste brasileiro e a seca de 2015 no leste da Amazônia. A análise das previsões prognósticas de 2017 a 2020 mostrou que os erros sistemáticos de superestimativa (subestimativa) de precipitação persistem em regiões como Amazônia, Sudeste e Sul do Brasil e norte da América do Sul (Nordeste brasileiro e sudeste da América do Sul). Similarmente, erros de subestimativa (superestimativa) de temperatura na maior parte do continente (Nordeste brasileiro e sudeste da América do Sul) permanecem nas previsões prognósticas. De forma geral, conclui-se que o modelo ECMWF-SEAS5 executa previsões sazonais de precipitação e temperatura para a América do Sul com considerável destreza e potencial para aplicações diversas. Entretanto, devem ser consideradas suas limitações e erros para melhor utilização de suas previsões

Development of tridimensional carbon fiber/epoxy composites reinforced through the thickness and the mechanical characterization of interlaminar fracture toughness and vibration properties

This study is focused on the assessment of the interlaminar fracture toughness in mode II and vibration mechanical properties of composites reinforced through the thickness with rectangular z-pinned manufactured by VARTM (Vacuum-assisted resin transfer molding) process. The influence of z-pinning in the mechanical properties of laminated structures is carried out and for the specimens with different z-pins sizes and pin areal densities are manufactured after Design of Experiment (DOE) matrix determination. For the composites fabricated without a polymeric mold, vibration properties z-pins reinforced composites demonstrated that the size and density of insertion of z-pins has a direct influence on the natural frequency of vibration, on the damping, or loss, and the amplitude of vibration. With the optimization made by the method of response surface (MSR), in a mono-objective analysis, it was demonstrated that it is possible to obtaining reductions in the maximum amplitude of forced vibration of 115%, and in an analysis multi objective has been shown that with a given insertion density and size of z-pins 81% reductions in maximum forced vibration amplitude and increases of 25% and 11% can be achieved damping factor and natural frequency of vibration, respectively. For the composites manufactured with polymeric mold, the fracture toughness in mode II was investigated and the results showed that pinning in composites improved the fracture resistance for all pinning proposals built. For the NPC (Non-precracked) step, the highest (GIIc)value achieved was for a 0.50 mm with a 2% pin density insertion, being 106% higher than the unpinned specimen. For the PC (Precracked) step, the thicker pins 1.00 mm and 1.10 mm acted again as a positive influence to mitigate the delamination and achieved elevated values of (GIIc), 77.5% and 78.3% higher than the unpinned specimen, respectively. The statistical results pointed that for the NPC case, the increase in density of pins always generates an increase in the fracture toughness and the contribution of the pin size to increase the fracture toughness. From there, increasing the size of the pin has little influence in NPC. For PC case, was shown that the pin size increasing decreases the fracture resistance, except for low pin density. Furthermore, the Artificial Neural Networks (ANN) trained with part of these experimental data showed excellent predictive capacity of fracture toughness. The modal responses of the laminates fabricated with a polymeric mold the experimental results indicated that, in most cases, there was an increase in the natural frequency and highlights the reduction, from approx. 60% to 70%, in the amplitude of vibration for all specimens with z-pin reinforcement in comparison to the unpinned. Furthermore, the experimental data compared the statistical results pointed that z pins had a positive influence increasing and decreasing natural frequency and forced vibration amplitude, respectively, of z-pinned composites compared to the non-reinforced and the trained ANN with the experimental data presented a very good agreement with experimental tests carried out in this investigation for predicting modal response.Este estudo tem como objetivo analisar a influência da inserção de z-pins retangulares com diferentes tamanhos e densidades de inserção, determinados pela matriz de experimentos de um Planejamento de Experimentos (DOE), nas propriedades mecânicas de tenacidade à fratura interlaminar em modo II e de vibrações de compósitos reforçados através da espessura fabricados por VARTM (Vacuum-assisted resin transfer molding). Para os compósitos fabricados sem molde polimérico, as propriedades de vibração dos compósitos reforçados com z-pins demonstraram que o tamanho e a densidade de inserção têm influência direta na frequência natural de vibração, no amortecimento e na amplitude de vibração. Com a otimização feita pelo método de superfície de resposta (MSR), em uma análise monoobjetiva, foi demonstrado que é possível obter reduções na amplitude máxima de vibração forçada de 115%, e em uma análise multiobjetiva foi demonstrado que com uma determinada densidade de inserção e tamanho dos z-pins têm-se 81% de redução na amplitude máxima de vibração forçada e aumentos de 25% e 11% podem ser alcançados no fator de amortecimento e na frequência natural de vibração, respectivamente. Para os compósitos fabricados com molde polimérico, a tenacidade à fratura em modo II foi investigada e os resultados mostraram que a inserção de z-pins aumentou a resistência à delaminação para todas os corpos de prova. Para a etapa NPC (Non-precracked), o maior valor de (GIIc) foi para o pino de 0,50 mm com inserção de 2%, sendo 106% superior ao corpo de prova sem reforço através da espessura. Para a etapa PC (Precracked), os pinos maiores com 1,00 mm e 1,10 mm atuaram novamente como uma influência positiva para mitigar a delaminação e atingiram valores elevados de (GIIc), 77,5% e 78,3% maiores que o corpo de prova sem pino, respectivamente. Os resultados estatísticos apontaram que para o caso NPC, o aumento da densidade de inserção sempre gera um aumento na tenacidade à fratura. A partir disto, aumentar o tamanho do pino tem pouca influência no NPC. Para a etapa PC foi demonstrado que o aumento do tamanho do pino diminui a resistência à fratura, exceto para baixa densidade de inserção. Além disso, as Redes Neurais Artificiais (Artifial Neural Network - ANN) treinadas com parte dos dados experimentais mostraram excelente capacidade preditiva das propriedades de tenacidade à fratura interlaminar. Para as respostas modais dos laminados fabricados com molde polimérico, os resultados experimentais indicaram que, na maioria dos casos, houve um aumento na frequência natural e houve uma redução, entre 60% a 70%, na amplitude de vibração para todos os corpos de prova reforçados com z-pins quando comparados aos sem reforço através da espessura. Além disso, os dados experimentais comparados com os resultados estatísticos apontaram que os z-pins tiveram uma influência positiva aumentando a frequência natural e diminuindo a amplitude de vibração forçada dos compósitos reforçados com z-pins, além disso, a ANN treinada com os dados experimentais apresentou concordância com os resultados dos testes experimentais realizados neste trabalho para se prever as respostas modais

Improved power losses calculation model for air core reactors

Air core reactors (ACR) have been widely used in power systems in several different applications like harmonic filters, thyristor-controlled reactors (TCR) for static var compensators (SVC), mechanically switched reactors (MSR) for shunt compensation of long transmission lines, smoothing and valve reactors for line commutate converter (LCC) and for voltage sourced converted (VSC), respectively, in HVDC systems, onshore and offshore. As a global trend, the pursuit of environmentally friendly equipment has increased, leveraging the use of ACRs in ultra-high voltage (UHV) systems. Applying that equipment in such voltage levels demands very accurate calculation models to establish the proper design parameters (e.g., inductance values, power losses and audible noise levels) as well as the stresses (dielectric, thermal and mechanical) that the equipment will have to withstand during operation, for their lifecycle. One typical concern related to those calculation models is regarding the prediction of the eddy current winding losses by analytical models. Several models have been proposed for this type of calculation for transformers and electrical machines, but usually with some constraints that make those models more suitable to that equipment than to others. With the crescent demand for ACR with lower power losses levels, it makes sense to look for improvements on those calculation models. One way of supporting the enhancement of those models is using software based on finite element methods (FEM) that allows for very detailed simulation of the physical phenomena related to the air core reactors and their applications. Although the FEM is a powerful tool for complex simulations, it is usually very time consuming and may require sophisticated computational apparatus to run more complex models. Air core reactors are equipment composed by one or several concentric windings made of conductive material (aluminum or copper) and their design may vary significantly, from a few kilograms to some dozens of tons. The simulation, in a reasonable time, of that equipment with several windings and sometimes thousands of turns would require computers that are not easily found in regular industries. In this work an optimized modeling process for simulating ACR using a 2-D equivalent geometry method in a finite element-based software was developed to allow for faster simulations. The validation of the method is performed by running a full factorial design of experiments (DOE), screening four design parameters of windings: winding diameter, winding height, number of strands and strand diameter, as these parameters significantly affect the two main design characteristics of the air core reactors: inductance and winding power losses. The results of the finite element simulations are statistically compared to the results of analytical calculations. With the deployment of this process, an improvement for the calculation of the eddy current winding losses of that equipment is proposed

Electromagnetic procedures to support main components design of synchronous machines

Synchronous generators have proven over the decades to be the feasible solution for three-phase power systems and have consolidated as the vital piece in power plants in which the source of energy is renewable, as hydraulic or wind. Thus, with a constant increase in environmental concerns in current times, it is also expected an increase in synchronous machine usage, along with more research and development. A challenge would be to integrate the traditional consolidated knowledge with modern computational tools. Since when it comes to electrical machines, there is more than one procedure or technique to solve the same question, many combinations of new algorithms and books from a century ago have yet space to be approached. This work proposes and develops a set of tools to allow the analysis of magnetics effects in a salient pole machine with general, accurate, and fast solutions, applying what has been taught for the first “machinerists”, as Tingley and Park, alongside with MATLAB and Finite Element Method. Its objectives are to get Magnetomotive Force and Magnetic Flux Density of a given machine so then, in future work, to calculate the inductance matrix. MMF is calculated through Tingley Box, Winding Matrix, and Fourier Series, allowing the analysis for every single turn. Flux density is calculated through Finite Element Analysis, which allows the calculation of enclosure factors that support the accuracy of the tool by comparing it with manufacturers' benchmarks. In the end, a guide in MATLAB is shown, which aggregates everything exposed with a user-friendly interface.Os geradores síncronos provaram ao longo das décadas ser a solução viável para sistemas elétricos trifásicos e se consolidaram como peça vital em usinas em que a fonte de energia é renovável, como hidráulica ou eólica. Assim, com um aumento constante das preocupações ambientais nos tempos atuais, também se espera um aumento no uso de máquinas síncronas, juntamente com mais pesquisa e desenvolvimento. Um desafio seria integrar o conhecimento tradicional consolidado com ferramentas computacionais modernas. Já que, quando se trata de máquinas elétricas, existe mais de um procedimento ou técnica para resolver a mesma questão, muitas combinações de novos algoritmos e livros de um século atrás ainda têm espaço para serem abordadas. Este trabalho propõe e desenvolve um conjunto de ferramentas para permitir a análise de efeitos magnéticos em uma máquina de pólo saliente com soluções gerais, precisas e rápidas, aplicando o que foi ensinado pelos primeiros “maquinistas”, como Tingley e Park, ao lado do MATLAB e Método dos Elementos Finitos. Seus objetivos são obter a Força Magnetomotriz e a Densidade do Fluxo Magnético de uma determinada máquina para então, em trabalhos futuros, calcular a matriz de indutância. O MMF é calculado por meio de Tingley Box, Matriz de enrolamento e Série de Fourier, permitindo a análise para cada curva. A densidade do fluxo é calculada por meio da Análise de Elementos Finitos, que permite o cálculo dos fatores de invólucro que suportam a precisão da ferramenta, comparando-a com os benchmarks dos fabricantes. Ao final, é apresentado um guia em MATLAB, que agrega tudo o que está exposto em uma interface amigável

Evaluating public policies for fair social tariff of electricity in brazil using na economic market model

Using an economic model of the electricity market (TAROT - Optimized Tariff) that represents the regulated market of distribution of electrical energy, this theses presents an evaluation of public policies for fare social tariffs of electricity in Brazil. It was considered the scenario of increasing number of prosumers (residential consumers who have self generation of electricity) in 2 of the 5 major regions of Brazil. The Brazilian regions have very different socioeconomic characteristics. However, the current electricity regulation is the same for all concessionaires. Because of the ineffectiveness of the existing tariff policy discount, in this work a new public policy is proposed, allowing the use of regulation in a different way in order to obtain the best result for Brazil and particularly for the poor population that today are not able to enjoy the benefits of electricity due to high tariff values. It is also discussed how this can contribute in a positive way to improve the income distribution in these regions, which is evaluated by using the Gini index.Agência 1Utilizando um modelo econômico do mercado de energia elétrica (TAROT - Tarifa Otimizada) que representa mercado regulado de distribuição de energia elétrica, esta tese apresenta um avaliação de políticas públicas de tarifas sociais de energia elétrica no Brasil. Foi considerado o cenário de aumento do número de prossumidores (consumidores residenciais que possuem geração de eletricidade) em 2 das 5 principais regiões do Brasil. As regiões brasileiras têm características socioeconômicas muito diferentes. No entanto, o regulamento de eletricidade atual é o mesmo para todas as concessionárias. Por causa da ineficácia da política tarifária existente desconto, neste trabalho é proposta uma nova política pública, permitindo a utilização da regulação em uma forma diferente para obter o melhor resultado para o Brasil e principalmente para os pobres população que hoje não consegue usufruir dos benefícios da energia elétrica devido à alta tarifa valores. Também é discutido como isso pode contribuir de forma positiva para a melhoria da renda distribuição nessas regiões, que é avaliada pelo índice de Gini

Driver’s behavior classification in vehicular communication networks for commercial vehicles

Vehicles are becoming more intelligent and connected due to the demand for faster, efficient, and safer transportation. For this transformation, it was necessary to increase the amount of data transferred between electronic modules in the vehicular network since it is vital for an intelligent system’s decision-making process. Hundreds of messages travel all the time in a vehicle, creating opportunities for analysis and development of new functions to assist the driver’s decision. Given this scenario, the dissertation presents the results of research to characterize driving styles of drivers using available information in vehicular communication network. This master thesis focuses on the process of information extraction from a vehicular network, analysis of the extracted features, and driver classification based on the extracted data. The study aims to identify aggressive driving behavior using real-world data collected from five different trucks running for a period of three months. The driver scoring method used in this study dynamically identifies aggressive driving behavior during predefined time windows by calculating jerk derived from the acquired data. In addition, the K-Means clustering technique was explored to group different behaviors into data clusters. Chapter 2 provides a comprehensive overview of the theoretical framework necessary for the successful development of this thesis. Chapter 3 details the process of data extraction from real and uncontrolled environments, including the steps taken to extract and refine the data. Chapter 4 focuses on the study of features extracted from the preprocessed data, and Chapter 5 presents two methods for identifying or grouping the data into clusters. The results obtained from this study have advanced the state-of-the-art of driver behavior classification and have proven to be satisfactory. The thesis addresses the gap in the literature by using data from real and uncontrolled environments, which required preprocessing before analysis. Furthermore, the study represents one of the pioneering studies conducted on commercial vehicles in an uncontrolled environment. In conclusion, this thesis provides insights into the development of driver behavior classification models using real-world data. Future research can build upon the techniques presented in this study and further refine the classification models. The thesis also addresses the threats to validity that were mitigated and provides recommendations for future research

Asymptotic symmetries and infrared phenomena in gauge theories and gravity

The objective of the following dissertation is to present the existent connection in the infrared regime behavior of both gauge theories and gravity. The first element in this picture analysis is the study of soft theorems, originally developed by Weinberg [1][2]. In a general sense, scattering processes are governed through constraints that control the way soft particles are produced. The second one shall be the asymptotic spacetime symmetries developed by Bondi, van der Burg, Metzner and Sachs [3] [4] of asymptotically flat spacetimes. They lead to the appearance of conserved charges associated to the behavior of the fields at null infinities. The third but not least, the existence of memory effects, like the ones studied by Christodolou [5][6] and Thorne [7] in the infrared limit. Again, in simple terms, they refer to the surgence of perturbations in the fabric of spacetime due to its propagation, leading to field shifts. We explore the connection in terms of the application of Fourier transforms and Ward identities. For simplicity we focus on the case of Quantum Electrodynamics and Quantum Gravity.O objetivo da seguinte dissertação é apresentar a conexão existente no comportamento do regime infravermelho em ambas as teorias de calibre e gravidade. O primeiro elemento desta análise é o estudo dos os teoremas soft , originalmente desenvolvidos por Weinberg [1][2]. Em um sentido geral, os processos de espalhamento são governados por meio de restrições que controlam a forma como as partículas soft são produzidas. O segundo elemento são as simetrias espaço-temporais assintóticas desenvolvidas por Bondi, van der Burg, Metzner e Sachs [3] [4] dos espaço-tempos assintoticamente planos. Eles fornecem o surgimento de cargas conservadas associadas ao comportamento dos campos através nos infinitos nulos. Terceiro, mas não menos importante, a existência de efeitos de memória, como os estudados por Christodolou [5][6] e Thorne [7] no limite infravermelho. Novamente, em termos simples, eles se referem ao surgimento de perturbações no tecido do espaço-tempo devido à sua propagação, levando a deslocamentos de campo. Nós exploramos a conexão em termos da aplicação de transformadas de Fourier e identidades de Ward. Por simplicidade, vamos-nos focar no caso da Eletrodinâmica Quântica e da Gravidade Quântica