This thesis describes an investigation into the influences of arcing and conductor deflection due to magnetic forces on the accuracy of fault locator algorithms in electrical distribution networks. The work also explores the possibilities of using the properties of an arc to identify two specific types of faults that may occur on an overhead distribution line. A new technique using the convolution operator is introduced for deriving differential equation algorithms. The first algorithm was derived by estimating the voltage as an array of impulse functions while the second algorithm was derived using a piecewise linear voltage signal. These algorithms were tested on a simulated single-phase circuit using a PI-model line. It was shown that the second algorithm gave identical results as the existing dynamic integration operator type algorithm. The first algorithm used a transformation to a three-phase circuit that did not require any matrix calculations as an equivalent sequence component circuit is utilised for a single-phase to ground fault. A simulated arc was used to test the influence of the non-linearity of an arc on the accuracy of this algorithm. The simulations showed that the variation in the resistance due to arcing causes large oscillations of the algorithm output and a 40th order mean filter was used to increase the accuracy and stability of the algorithm. The same tests were performed on a previously developed fault locator algorithm that includes a square-wave power frequency proximation of the fault arc. This algorithm gave more accurate and stable results even with large arc length variations. During phase-to-phase fault conditions, two opposing magnetic fields force the conductors outwards away from each other and this movement causes a change in the total inductance of the line. A three dimensional finite element line model based on standard wave equations but incorporating magnetic forces was used to evaluate this phenomenon. The results show that appreciable errors in the distance estimations can be expected especially on poorly tensioned di stribution lines.New techniques were also explored that are based on identification of the fault arc. Two methods were successfully tested on simulated networks to identify a breakingconductor. The methods are based on the rate of increase in arc length during the breaking of the conductor. The first method uses arc voltage increase as the basis of the detection while the second method make use of the increase in the non-linearity of the network resistance to identify a breaking conductor. An unsuccessful attempt was made to identifying conductor clashing caused by high winds: it was found that too many parameters influence the separation speed of the two conductors. No unique characteristic could be found to identify the conductor clashing using the speed of conductor separation. The existing algorithm was also used to estimate the voltage in a distribution network during a fault for power quality monitoring purposes.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Protection systems used in distribution networks of electricity are not able to detect short circuits with high contact resistance due to the low currents generated, endangering the population and degrading the quality of the energy supplied. In this sense, this paper presents a new methodology for detecting high-impedance faults (HIF) in distribution networks. The developed algorithm has the main advantage the fact also detect and classify other types of transient as, for example, switching capacitor banks, transformers and loads. This characteristic decreases the improper operation caused by transient switching. Another feature of the developed method is no need to install additional equipment on the network which greatly reduces the cost of implementation. Additionally, the paper also discusses the causes, consequences and characteristics of HIF in order to evidence the difficulties related to their detection. A brief review of the models proposed in the literature for computational simulation of HIF is also discussed, and the model used in this work is described in detail. To evaluate the performance of the algorithm developed a series of tests with different fault scenarios high impedance were made. Furthermore, other various types of transients that are normal in the feeders were tested. The good results obtained, combined the simplicity of the method and does not need to install additional equipment feeders, makes a promising technique for real applications. / Os sistemas de proteção utilizados em redes de distribuição de energia elétrica não são capazes de detectar curtos-circuitos com alta resistência de contato devido às reduzidas correntes geradas, colocando em risco a população e degradando a qualidade da energia fornecida. Neste sentido, este trabalho visa apresentar uma nova metodologia para detecção de faltas de alta impedância (FAI) em redes de distribuição de energia elétrica. O algoritmo desenvolvido possui como principal vantagem o fato de também detectar e classificar outros tipos de transitórios como, por exemplo, chaveamento de banco de capacitores, transformadores e manobras de ramais. Essa característica diminui consideravelmente as atuações indevidas causadas por transitórios oriundos de manobras. Outra característica do método desenvolvido é a não necessidade de instalação de equipamentos adicionais na rede, o que reduz consideravelmente o custo de sua implementação. Além disso, o trabalho também aborda as causas, consequências e características das FAI de forma a evidenciar as dificuldades relacionadas à sua detecção. Uma breve revisão sobre os modelos propostos na literatura para simulação computacional de FAI também é abordado, sendo que o modelo utilizado nesse trabalho é descrito em detalhes. Para avaliar o desempenho do algoritmo desenvolvido, uma série de testes com diferentes cenários de falta de alta impedância foram realizados. Além disso, outros tipos de transitórios que são normais nos alimentadores foram testados. Os bons resultados obtidos, aliado a simplicidade do método e a não necessidade de instalação de equipamentos adicionais nos alimentadores, torna a técnica promissora para aplicações reais.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-05-07T20:46:33Z No. of bitstreams: 1 WELLINSÍLVIO COSTA DOS SANTOS – TESE (PPGEE) 2016.pdf: 10591682 bytes, checksum: 97299060f7fb8f9c7f837b25352da777 (MD5) / Made available in DSpace on 2018-05-07T20:46:33Z (GMT). No. of bitstreams: 1 WELLINSÍLVIO COSTA DOS SANTOS – TESE (PPGEE) 2016.pdf: 10591682 bytes, checksum: 97299060f7fb8f9c7f837b25352da777 (MD5) Previous issue date: 2016-08-15 / Capes / Uma técnica baseada em análise de transitórios eletromagnéticos é proposta para identificar faltas de alta impedância (FAI) em redes de distribuição. O algoritmo dispensa conhecimento dos parâmetros dos alimentadores e faz uso da transformada wavelet discreta (TWD) para monitorizar fenômenos transitórios associados a distúrbios no sistema de distribuição. A metodologia proposta é avaliada através de simulações em um programa de transitórios eletromagnéticos (EMTP) em um sistema de 13,8 kV, que foi modelado a partir de dados de uma rede de distribuição brasileira real. Além de FAI, foram simulados outros tipos de distúrbios, tais como faltas de baixa impedância, chaveamentos de novas linhas e bancos de capacitores. Os resultados obtidos demonstraram que o método é capaz de detectar a perturbação logo após o seu início e distingui-la de outros distúrbios, além de proporcionar uma redução significativa da região de localização da FAI. / An electromagnetic transient analysis-based technique is proposed to identify high impedance faults (HIF) in distribution networks. The algorithm dispenses knowledge of the feeder parameters and makes use of discrete wavelet transform (TWD) to monitor transient phenomena associated with disturbances in the distribution system. The proposed methodology is evaluated through simulations in an electromagnetic transient program (EMTP) in a 13.8 kV system, which was modeled from actual Brazilian distribution network data. Besides HIF, other types of disturbances were simulated, such as low impedance fault, and switching of lines and capacitor banks. Obtained results have shown that the method is able to detect the disturbance soon after its inception and distinguish it from other disorders, as well as providing a significant reduction in the region of its location for maintenance crews.

Made available in DSpace on 2014-12-17T14:54:58Z (GMT). No. of bitstreams: 1 DaviBB_DISSERT_1-70.pdf: 4567680 bytes, checksum: 150ff5afc1806ca374278b4c00a1f5a3 (MD5) Previous issue date: 2010-12-06 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Metamaterials exhibiting negative refraction have attracted a great amount of attention in recent years mostly due to their exquisite electromagnetic properties. These materials are artificial structures that exhibit characteristics not found in nature. It is possible to obtain a metamaterial by combining artificial structures periodically. We investigated the unique properties of Split Ring Resonators, High impedance Surfaces and Frequency Selective Surfaces and composite metamaterials. We have successfully demonstrated the practical use of these structures in antennas and circuits. We experimentally confirmed that composite metamaterial can improve the performance of the structures considered in this thesis, at the frequencies where electromagnetic band gap transmission takes place

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-12-07T12:33:00Z No. of bitstreams: 1 lucianacarvalhoacacio.pdf: 3829408 bytes, checksum: 88a83782335531c4be76d1544699c7bb (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-12-22T11:27:58Z (GMT) No. of bitstreams: 1 lucianacarvalhoacacio.pdf: 3829408 bytes, checksum: 88a83782335531c4be76d1544699c7bb (MD5) / Made available in DSpace on 2017-12-22T11:27:58Z (GMT). No. of bitstreams: 1 lucianacarvalhoacacio.pdf: 3829408 bytes, checksum: 88a83782335531c4be76d1544699c7bb (MD5) Previous issue date: 2017-08-25 / Este trabalho propõe um método baseado em algoritmos genéticos para alocação ótima de medidores na rede. A partir da alocação dos medidores, é verificado a assertividade alcançada na detecção de defeitos monofásicos, por área, com impedância na média tensão de sistemas de distribuição. Assim, é avaliado o desempenho da metologia de alocação ótima dos medidores. A saída do algoritmo, indica as posições que os medidores devem ser alocados, que formarão as respectivas áreas de observações para detecção. Para realizar a detecção de defeitos em sistemas de distribuição foi desenvolvido também um método utilizando redes neurais artificiais, que é utilizado como rotina interna do método de alocação de medidores, onde as entradas são grandezas elétricas de tensão e corrente, podendo ser medições fasoriais e/ou não-fasoriais, oriundas dos medidores definidos no método de alocação. Esta variação de tipos de medições serviu para analisar o desempenho na detecção do defeito do emprego de diferentes tipos de equipamentos de medição. A escolha da detecção de defeitos monofásicos é baseada no fato de que estes são a grande maioria nos sistemas de distribuição. O método desenvolvido consegue detectar defeitos monofásicos com resistência de arco variando entre 0 a 200 ohms, considerando ainda, variação do carregamento do sistema. O método proposto para alocação, bem como a rotina para detecção de falhas foi desenvolvido no ambiente MatLab®. Os testes foram realizados em sistemas do IEEE, apresentando bons resultados. / The proposal of this work is to develop a method based on genetic algorithms for optimal allocation of measurements units the distribution grid, which aims to detect monophasic defects with impedance in the medium voltage of distribution systems. The detection is performed by artificial neural networks. The developed methodology for optimal distribution of meters indicates as output the positions that the units should be allocated, creating detection areas. Artificial neural networks were used to perform fault detection in distribution systems, which is an internal routine of the measurement units distribution method. The inputs of the artificial neural networks are voltage and current. These electrical parameters can be either phasor measurements and/or non-phasor, depending on the category of meters defined in the allocation algorithm. The performance of different types of measurement equipment was executed by the analysis of different measurement types. It was selected single-phase defects due to the fact that these are the vast majority of faults in distribution systems. The developed method is able to identify single-phase defects with arc resistance ranging from 0 to 200 ohms, and it is also capable of correctly detect faults when considering load variation. The method of measurement unit allocation and the fault detection algorithm were developed in the software MatLab®. Tests were performed in IEEE systems, presenting good results.

Os sistemas elétricos de potência modernos apresentam inúmeros desafios em sua operação. Nos sistemas de distribuição de energia elétrica, devido à grande ramificação, presença de extensos ramais monofásicos, à dinâmica das cargas e demais particularidades inerentes, a localização de faltas representa um dos maiores desafios. Das barreiras encontradas, a influência da impedância de falta é uma das maiores, afetando significativamente a aplicação dos métodos tradicionais na localização, visto que a magnitude das correntes de falta é similar à da corrente de carga. Neste sentido, esta tese objetivou desenvolver um sistema inteligente para localização de faltas de alta impedância, o qual foi embasado na aplicação da técnica de decomposição por componentes ortogonais no pré-processamento das variáveis e inferência fuzzy para interpretar as não-linearidades do Sistemas de Distribuição com presença de Geração Distribuída. Os dados para treinamento do sistema inteligente foram obtidos a partir de simulações computacionais de um alimentador real, considerando uma modelagem não-linear da falta de alta impedância. O sistema fuzzy resultante foi capaz de estimar as distâncias de falta com um erro absoluto médio inferior a 500 m e um erro absoluto máximo da ordem de 1,5 km, em um alimentador com cerca de 18 km de extensão. Tais resultados equivalem a um grau de exatidão, para a maior parte das ocorrências, dentro do intervalo de ±10%. / Modern electric power systems present numerous challenges in its operation. Fault location is a major challenge in Power Distribution Systems due to its large branching, presence of single-phase laterals and the dynamic loads. The influence of the fault impedance is one of the largest, significantly affecting the use of traditional methods for its location, since the magnitude of the fault currents is similar to the load current. In this sense, this thesis aimed to develop an intelligent system for location of high impedance faults, which was based on the application of the decomposition technique of orthogonal components in the pre-processing variables and fuzzy inference to interpret the nonlinearities of Power Distribution Systems with the presence of Distributed Generation. The data for training the intelligent system were obtained from computer simulations of an actual feeder, considering a non-linear modeling of the high impedance fault. The resulting fuzzy system was able to estimate distances to fault with an average absolute error of less than 500 m and a maximum absolute error of 1.5 km order, on a feeder about 18 km long. These results are equivalent to a degree of accuracy for the most occurrences within the ± 10% range.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-04-11T15:15:34Z No. of bitstreams: 1 joaotitoalmeidavianna.pdf: 4307092 bytes, checksum: 061d2a47a7e37bf6c1a1875c27f352ad (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-04-18T12:47:46Z (GMT) No. of bitstreams: 1 joaotitoalmeidavianna.pdf: 4307092 bytes, checksum: 061d2a47a7e37bf6c1a1875c27f352ad (MD5) / Made available in DSpace on 2017-04-18T12:47:46Z (GMT). No. of bitstreams: 1 joaotitoalmeidavianna.pdf: 4307092 bytes, checksum: 061d2a47a7e37bf6c1a1875c27f352ad (MD5) Previous issue date: 2016-09-05 / O presente trabalho tem por objetivo o desenvolvimento de alternativas para detecção de faltas de alta impedância (HIFs) sustentadas em sistemas de distribuição. Como a maioria destas faltas é monofásica, enfoque foi dado para este tipo de falta no desenvolvimento do trabalho. Devido ao desequilíbrio e a variação da carga dos sistemas de distribuição, a proteção tradicional dos mesmos apresenta dificuldades na detecção destas faltas, que acabam se sustentando no sistema. Isso acarreta um risco de segurança pública, na medida em que estruturas externas ao sistema elétrico são mantidas energizadas representando risco a vidas que entrem em contato com elas. Características da topologia típica de sistemas de distribuição brasileiros (conhecida como do “tipo europeu”) foram exploradas de forma a se elaborar duas propostas de métodos de detecção e localização de HIFs. Ambos os métodos se baseiam na alocação de medidores alocados ao longo do sistema de distribuição, cujas medidas são integradas a uma central de dados via rede de comunicação. Nesta central, as medidas recebidas são analisadas de forma a diagnosticar a presença e localização de faltas monofásicas de alta impedância no sistema e emitir alarmes que descrevam a situação atual do mesmo. O primeiro método, o PDSZ, baseia-se em medições fasoriais sincronizadas e, além da detecção e localização, conta com um algoritmo de classificação das fases envolvidas na falta. Já o segundo (PQDSZ) baseia-se em medições não fasoriais e não possui esta última funcionalidade. Ambos os métodos são implementados em laboratório e simulados com o uso de um Simulador Digital de Tempo Real (RTDS), o que permite uma validação bem próxima da aplicação dos métodos em um sistema real. Tais simulações comprovam a aplicabilidade dos métodos propostos e todos os resultados são analisados de forma a confirmar este fato. / This work aims to develop alternatives for the detection of sustained high impedance faults (HIFs) on distribution power systems. As the majority of these faults are single phase ones, the development was focused on this kind of fault. Due to load unbalance and variation of the distribution systems, the traditional protectiontechniques presents problems on detecting these faults, which are kept sustained on the system. This situation represents a serious public hazard, because the external electrical system structure remains energized, representing a risk to lives that eventually get in touch with it. There is also the risk of starting a fire from this fault point. Topologycal features of Brasilian distribution systems (known as “european type”) were exploited in order to elaborate two methods for detection and localization of HIFs. Both methods are based on the use of meters alocated along the distribution system, whose measurements are sent to a central data concentrator, through a network communication. Then, the received measurements are analysed in order to diagnose the ocurrence of single phase high impedance faults on the system and send alarms that describe the current system situation. The first method, named PDSZ, is based on Phasor Measurement Units (PMUs) and besides detecting and locating the fault, can also classify it, showing which phaseis involved. The second one, the PQDSZ, is based on non-synchronized measurements and can not classify the fault. Both methods were implemented on laboratory and tested using real equipament and a Real Time Digital Simulator (RTDS), which allows a very precise evaluation of the proposed methods, emulating conditions very similar the real ones. The simulations prove the aplicability of the proposed methods and the results are analysed in order to show the effectiveness of the proposed methods.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-05-18T13:24:16Z No. of bitstreams: 1 jorgejaviergimenezledesma.pdf: 4002237 bytes, checksum: 74e94889e9e4afbc4463915274bf7e33 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-05-18T14:07:36Z (GMT) No. of bitstreams: 1 jorgejaviergimenezledesma.pdf: 4002237 bytes, checksum: 74e94889e9e4afbc4463915274bf7e33 (MD5) / Made available in DSpace on 2017-05-18T14:07:36Z (GMT). No. of bitstreams: 1 jorgejaviergimenezledesma.pdf: 4002237 bytes, checksum: 74e94889e9e4afbc4463915274bf7e33 (MD5) Previous issue date: 2017-02-12 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Este trabalho propõe o desenvolvimento de modelos e métodos numéricos, baseados em redes neurais artificiais, para a detecção e localização de áreas com defeitos de alta impedância em sistemas de distribuição. De forma paralela, também é avaliada a eficiência da utilização de diferentes tipos de formas de medição de dados no desempenho do método, que é implementada através de duas etapas. A primeira etapa consiste na adaptação de um programa existente para cálculo de faltas, tendo como objetivo gerar de forma aleatória vários tipos de defeitos, assim como a localização dos mesmos. A metodologia de cálculo de defeitos foi desenvolvida utilizando as equações de injeção de correntes em coordenadas retangulares. Neste programa, também serão considerados os modelos de carga variantes com a tensão durante os defeitos e modelos de diversas gerações distribuídas, convencionais e não convencionais. Em seguida, foi desenvolvido e implementado um método baseado em redes neurais artificiais, para detecção e identificação de faltas, assim como para estimar a localização de faltas em um sistema de distribuição. Esta rede neural possui como entrada módulos e ângulos das tensões e correntes do sistema elétrico, obtidas através das medições fasoriais dos PMUs e/ou IEDs. As saídas da rede neural correspondem à detecção e localização de áreas de defeitos. O método proposto foi desenvolvido no ambiente MatLab® e com o intuito de avaliar sua eficiência, foi testado em alguns sistemas IEEE e em um sistema real. Os resultados obtidos dos estudos são apresentados sob a forma de tabelas e gráficos com suas respectivas acurácias, números de neurônios e as diferentes configurações adotadas. / This work proposes the development of numerical models and methods, based on artificial neural networks, for the detection and localization of high impedance faults in distribution systems. In parallel, the efficiency is also evaluated using different types of measurement data techniques in the performance of the method, which is implemented through two steps. The first step consists in the adaptation of an existing program for calculation of faults, aiming to generate randomly several types of faults, as well as their location. The faults calculation methodology was developed using current injection equations in rectangular coordinates. In this program the models of load variation with the voltage during the faults and a variety of conventional and unconventional models for distributed generation, are considered. Next, a method based on artificial neural networks is developed and implemented for the detection and identification of faults, as well as to estimate the fault location within a distribution system. The neural network inputs are modules and angles of the voltages and currents of the electrical system, obtained from the PMUs and / or IEDs. The outputs of the neural network correspond to the detection and location of faults. The proposed method was developed in MatLab® environment and tested in some IEEE systems and in a real system in order to evaluate its efficiency. The results obtained from the studies was presented in the form of tables and graphs with their respective accuracy, numbers of neurons and the different configurations adopted.

The process industries span multiple industrial sectors and constitute a substantial part of the entire manufacturing industry. Since companies belonging to this family of industries are often very asset intensive, their ability to respond to changes is often limited in the short term. The adaptation of the capabilities of existing processes, and conversely finding products and market segments to match the production system capabilities, are an important part of product- and market development activities in the process industry. The importance to companies in the process industry of having a well-articulated manufacturing strategy congruent with the business strategy is second to none. However, to facilitate manufacturing strategy developments, it is essential to start with an improved characterization and understanding of the material transformation system. To that end an extensive set of variables was developed and related measures and scales were defined. The resulting configuration model, focusing on company generic process capabilities in the process industries, is to be regarded as a conceptual taxonomy and as a proposition available for further testing. The usability of the model was subsequently assessed using “mini-cases” in the forestry industry, where the respondents confirmed that the company’s overall strategy could benefit from this kind of platform as a possible avenue to follow. The model was deployed as an instrument in the profiling of company material transformation systems to facilitate the further development of companies' functional and business strategies. The use of company-generic production capabilities was studied in three case companies representing the mineral, food and steel industries. The model was found by the respondents to be usable as a knowledge platform to develop production strategies. In the final analysis of the research results, a new concept emerged called “production capability configuration": A process-industrial company’s alignment of its generic production capabilities in the areas of raw materials, process technology and products to improve the consistency among the variable elements that define operations and improve the congruence between operations and its environment. From the perspective of value creation and capture, firms must be able to manufacture products in a competitive cost structure within the framework of a proper business model. By using the configuration model, the relationship between manufacturing and innovation activities has been studied in the previously mentioned three case studies. In many cases the gap in capability appears as a limitation in the production system, requiring development efforts and sometimes investments to overcome. This is illustrated with two examples from the steel industry, where development efforts of the production system capabilities are initiated to better match the market demands. One example is the increase the volume- and product flexibility of an existing stainless steel melt shop, resulting in a proposed oblong Argon Oxygen Decarburisation (AOD) converter configuration that was subsequently verified using water modelling. The second example is from a carbon steel mill, where the target was to increase the raw material- and volume flexibility of another melt shop, by modifying the capabilities of the Electric Arc Furnace (EAF). Enabling EAF technologies are further described and evaluated using operational data and engineering type of estimates. / <p>QC 20170116</p>

The doctoral thesis presents methods for low-level measurements, which are exemplified by the general measurement of air ion concentration. Within the first section, the author progressively identifies certain critical effects influencing the concentration of air ions, and these effects are to be considered in evaluating the uncertainty of the measured concentrations. Thus, the thesis aims to provide a systematic description of the procedures and requirements related to low-level measurements; the proposed description then involves a discussion of the process reliability requirements, namely the factors of repeatability, elimination of errors, and definition and describability of measurement uncertainties. Such methodology facilitates, among other activities, the long-term monitoring of air ion concentration in extreme environments, including caves or spaces characterized by high temperatures and humidity. The use of common methods for determining the air ion mobility spectrum is accompanied by a number of disturbing effects, such as spurious fluctuation in the concentration of air ions in time. The experimental section of the thesis describes the testing of different configurations of the measuring device (a collecting electrode and a polarization capacitor); at this stage, we seek the most advantageous distribution of the electrostatic field in the sensor – a Gerdien tube. The systematic suppression of the influence of spurious fluctuations in air ion concentration during the measurement of saturation characteristics is carried out with the least-squares numerical method (as a supporting element), a hybrid technique to describe and evaluate the experimental model. In the second part of the thesis, the methodology of low-level measurement is complemented with procedures for the measurement of freezing potential. This latter domain, as an overall experimental approach applicable during phase changes of the sample, has hitherto not been sufficiently characterized from the metrological perspective, in an up-to-date manner; several subregions of the said domain remain somewhat obscured and deserve significantly more attention. In the given context, this thesis systematically considers a problem where comparable measurement results produced by multiple authors are not available. The measuring methodology proposed herein was utilized in applied research to facilitate the fabrication of an apparatus for the experimental measurement of freezing potential in pre-defined samples; the obtained results then lead us to conclusions with respect to the evaluation of effects that cause differences in the measured data, and the results can be further compared with those obtained by other researchers investigating the given segment of the problem.