This dissertation presents the development of an algorithm for classifying electrical transients in power transformers for protection. Initially the main transient involving power transformers were analyzed, with a special focus on the magnetizing current that occur during energizing equipment, known as inrush currents. Among the studied transient, current inrush are those that present greater difficulty in identification and discrimination by the differential protection, due to its high peak magnitude. In a second moment, was developed a test system implemented in ATP / EMTP software for the simulation of different operating situations of the power transformer, current data being obtained from TCs for analysis. After known the problem and implement a test for acquisition system, we developed an algorithm based on the last samples of the detail coefficients, called Details Signals, from the decomposition of the data of differential phase current using the Discrete Wavelet Transform. The methodology has the objective improve the system for protection of the transformer, becoming one efficient alternative for the identification of transients. / Esta dissertação apresenta o desenvolvimento de um algoritmo para classificação de transitórios elétricos em transformadores de potência, para fins de proteção. Inicialmente foram analisados os principais transitórios associados aos transformadores de potência, tendo um foco especial na corrente de magnetização que surge durante a energização do equipamento, conhecida como corrente de inrush. Dentre os transitórios estudados, as correntes de inrush são as que apresentam maior dificuldade de identificação e discriminação por parte da proteção diferencial, devido a sua alta magnitude de pico. Em um segundo momento, foi desenvolvido um sistema teste implementado no software ATP para a simulação das diversas situações de operação do transformador de potência, sendo obtidos dados de correntes a partir dos TCs para análise. Após conhecer o problema e implementar um sistema teste para a obtenção dos dados, desenvolveu-se um algoritmo baseado nas últimas amostras dos coeficientes de detalhes, chamada de Sinais de Detalhes, provenientes da decomposição dos dados de correntes diferenciais das fases por meio da Transformada Wavelet Discreta. A metodologia desenvolvida tem como objetivo melhorar o sistema de proteção do transformador, tornando-se uma alternativa eficiente para a identificação de transitórios.

Transformadores de potência são dispositivos que requerem atenção especial devido a sua grande importância ao sistema elétrico de potência no qual ele está conectado. Geralmente relés diferenciais são utilizados como proteção primária em transformadores de potência. Nestes relés, a corrente diferencial é comparada com um nível de ajuste e caso ocorra uma falta interna, o transformador deverá ser desconectado do restante do sistema. Entretanto, a simples detecção da presença de uma corrente diferencial não é suficiente para distinguir faltas internas de outras situações que também podem produzir tal corrente. Tais situações surgem durante a energização dos transformadores, devido a saturação dos transformadores de corrente, entre outras, as quais podem resultar em uma incorreta atuação da proteção. Uma rápida e correta discriminação entre faltas internas e outras situações é um dos desafios da moderna proteção de transformadores de potência. A respeito da identificação de faltas internas ou situações de energização, além da mencionada lógica diferencial é acrescentado uma subrotina baseada na restrição de harmônicas. Neste método, a corrente de energização é reconhecida através da presença de uma segunda harmônica obtida por filtros de Fourier. No entanto, o método de filtragem pode algumas vezes retardar a operação da proteção. Além disto, uma componente de segunda harmônica pode também estar presente durante uma falta interna. Este trabalho propõe a utilização da transformada Wavelet - uma poderosa ferramenta matemática - empregada como um meio rápido e eficiente de analisar as formas de onda de transformadores de potência e como uma alternativa a tradicional transformada de Fourier. Os sinais das correntes diferenciais são processados pelas transformadas discretas Wavelet, visando obter uma discriminação entre ambas situações (energização e falta). Um nível de limiar é utilizado após a decomposição Wavelet do sinal para discriminar entre as situações descritas. A janela de dados utilizada para este propósito pode ser variada. Para testar o algoritmo proposto, as simulações de energização e falta foram implementadas, utilizando o programa ATP (\"Alternative Transient Program\"). Em situações onde a janela de dados é reduzida para 1/4 de ciclo o critério de discriminação pode ser otimizado utilizando a transformada discreta de Wavelet auxiliada com técnicas de reconhecimento de padrões. Este trabalho apresenta a utilização de redes neurais artificiais para tal finalidade como exemplo. Resultados encorajadores são apresentados sobre a capacidade de discriminação para as situações descritas assim como a rapidez de resposta quando comparados aos métodos tradicionais. / Power transformers are devices that require special maintenance and care due to their importance to the electrical system to which they are connected. Generally, differential relays are used for the primary protection of large transformers. In such relays, differential currents are compared to a threshold and in the case of an internal fault, the transformer should be disconnected from the rest of the system. However, a simple detection of a differential current is not sufficient to distinguish internal faults from other situations that also produce such a current. Some of these situations appear during transformer energization (inrush currents), CT (current transformer) saturation, among others, which can result in an incorrect trip. A correct and fast distinction of internal faults from the other situations mentioned is one of the challenges for modern protection of power transformers. Concerning the identification of internal faults as opposed to inrush currents, the approach tarditionally used is the aforementioned differential logic together with harmonic restraint. In this method, transformer inrush current due to energization is recognized on the basis of second harmonic components obtained by Fourier filters. However, the filtering method can sometimes delay the protection process. In addition to this, a second harmonic component can also be present during internal faults. This work proposes Wavelet transform - a powerful mathematical tool - employed as a fast and effective means of analyzing waveforms from power transformers, as an alternative to the traditional Fourier transform. The differential signals are processed by discrete Wavelet transform to obtain the discrimination between both situations (inrush and fault). A threshold level is utilized after the Wavelet decomposition to discriminate the situations describeb. The time window used for such purpose can be varied. In order to test proposed algorithm, simulations of fault and inrush currents in a power transformer were implemented using ATP ( \"Alternative Transient Program\") software. When the time window is reduced to only 1/4 of the cycle the discrimination criteria should be optimized using a pattern recognition technique to aid the Discrete Wavelet transform. This study shows as a sample for this purpose the use of artificial neural networks. Very encouraging results are presented concerning the capacity of discrimination of the described situations as well as the speed of response when compared to the traditional method.

Current differential protection principle is superior in terms of sensitivity and speed of operation in comparison with other protection principle used in power systems. From the last five decades, various current differential protection schemes are widely used to protect busbars, transformers, and short-transmission lines. The deployment of high capacity microwave and optical fiber technologies redefined the line protection systems by facilitating the use of current differential protection schemes for long transmission lines. The common application issue of these schemes is mis-operation due to current transformer (CT) saturation during close-in external faults. Moreover, transformer differential protection schemes face mis-trip due to inrush current during energization. The techniques presented in the literature to address those issues, de-sensitize protection function and increase the time of operation. A comprehensive fault discrimination algorithm and an inrush current detection algorithm are highly demanded for current differential protection schemes. The purpose of this dissertation is to optimize the performance of differential schemes applied to protect busbar, transformer and line. This research derives the mathematical model of saturated secondary current of CT and introduces the concept of Partial Operating Current (POC). Based on these mathematical developments, the characteristics of POC are identified for all three types of differential zones like busbar, transformer and line protection. A new inrush current blocking algorithm is developed for transformer differential protection. A new time-domain CT saturation detection algorithm is also proposed. Based on these new developments, three separate differential schemes are designed for busbar, transformer, and line protection, respectively. The proposed schemes provide complete immunity against the mis-operations due to CT saturation during close-in external faults and transformer inrush current without sacrificing the sensitivity for internal faults. The speed of operation is also improved. The model for each scheme is built in Matlab platform and the performance is validated using the test system simulated in Electro-Magnetic Transient Program (EMTP) for all possible fault scenarios. Documented results show the improved performance of the proposed schemes when compared to traditional differential schemes in terms of reliability, sensitivity, selectivity, and speed

No description available.

Transformadores de potência são dispositivos que requerem atenção especial devido a sua grande importância ao sistema elétrico de potência no qual ele está conectado. Geralmente relés diferenciais são utilizados como proteção primária em transformadores de potência. Nestes relés, a corrente diferencial é comparada com um nível de ajuste e caso ocorra uma falta interna, o transformador deverá ser desconectado do restante do sistema. Entretanto, a simples detecção da presença de uma corrente diferencial não é suficiente para distinguir faltas internas de outras situações que também podem produzir tal corrente. Tais situações surgem durante a energização dos transformadores, devido a saturação dos transformadores de corrente, entre outras, as quais podem resultar em uma incorreta atuação da proteção. Uma rápida e correta discriminação entre faltas internas e outras situações é um dos desafios da moderna proteção de transformadores de potência. A respeito da identificação de faltas internas ou situações de energização, além da mencionada lógica diferencial é acrescentado uma subrotina baseada na restrição de harmônicas. Neste método, a corrente de energização é reconhecida através da presença de uma segunda harmônica obtida por filtros de Fourier. No entanto, o método de filtragem pode algumas vezes retardar a operação da proteção. Além disto, uma componente de segunda harmônica pode também estar presente durante uma falta interna. Este trabalho propõe a utilização da transformada Wavelet - uma poderosa ferramenta matemática - empregada como um meio rápido e eficiente de analisar as formas de onda de transformadores de potência e como uma alternativa a tradicional transformada de Fourier. Os sinais das correntes diferenciais são processados pelas transformadas discretas Wavelet, visando obter uma discriminação entre ambas situações (energização e falta). Um nível de limiar é utilizado após a decomposição Wavelet do sinal para discriminar entre as situações descritas. A janela de dados utilizada para este propósito pode ser variada. Para testar o algoritmo proposto, as simulações de energização e falta foram implementadas, utilizando o programa ATP (\"Alternative Transient Program\"). Em situações onde a janela de dados é reduzida para 1/4 de ciclo o critério de discriminação pode ser otimizado utilizando a transformada discreta de Wavelet auxiliada com técnicas de reconhecimento de padrões. Este trabalho apresenta a utilização de redes neurais artificiais para tal finalidade como exemplo. Resultados encorajadores são apresentados sobre a capacidade de discriminação para as situações descritas assim como a rapidez de resposta quando comparados aos métodos tradicionais. / Power transformers are devices that require special maintenance and care due to their importance to the electrical system to which they are connected. Generally, differential relays are used for the primary protection of large transformers. In such relays, differential currents are compared to a threshold and in the case of an internal fault, the transformer should be disconnected from the rest of the system. However, a simple detection of a differential current is not sufficient to distinguish internal faults from other situations that also produce such a current. Some of these situations appear during transformer energization (inrush currents), CT (current transformer) saturation, among others, which can result in an incorrect trip. A correct and fast distinction of internal faults from the other situations mentioned is one of the challenges for modern protection of power transformers. Concerning the identification of internal faults as opposed to inrush currents, the approach tarditionally used is the aforementioned differential logic together with harmonic restraint. In this method, transformer inrush current due to energization is recognized on the basis of second harmonic components obtained by Fourier filters. However, the filtering method can sometimes delay the protection process. In addition to this, a second harmonic component can also be present during internal faults. This work proposes Wavelet transform - a powerful mathematical tool - employed as a fast and effective means of analyzing waveforms from power transformers, as an alternative to the traditional Fourier transform. The differential signals are processed by discrete Wavelet transform to obtain the discrimination between both situations (inrush and fault). A threshold level is utilized after the Wavelet decomposition to discriminate the situations describeb. The time window used for such purpose can be varied. In order to test proposed algorithm, simulations of fault and inrush currents in a power transformer were implemented using ATP ( \"Alternative Transient Program\") software. When the time window is reduced to only 1/4 of the cycle the discrimination criteria should be optimized using a pattern recognition technique to aid the Discrete Wavelet transform. This study shows as a sample for this purpose the use of artificial neural networks. Very encouraging results are presented concerning the capacity of discrimination of the described situations as well as the speed of response when compared to the traditional method.

Submitted by camilla martins (camillasmmartins@gmail.com) on 2017-01-27T15:47:00Z No. of bitstreams: 1 Tese_AnaliseEstressesEletromagneto-Mecanicos.pdf: 15599744 bytes, checksum: 20d027f9186083e307e7bd5b07dd37a0 (MD5) / Approved for entry into archive by Edisangela Bastos (edisangela@ufpa.br) on 2017-01-30T12:42:38Z (GMT) No. of bitstreams: 1 Tese_AnaliseEstressesEletromagneto-Mecanicos.pdf: 15599744 bytes, checksum: 20d027f9186083e307e7bd5b07dd37a0 (MD5) / Made available in DSpace on 2017-01-30T12:42:38Z (GMT). No. of bitstreams: 1 Tese_AnaliseEstressesEletromagneto-Mecanicos.pdf: 15599744 bytes, checksum: 20d027f9186083e307e7bd5b07dd37a0 (MD5) Previous issue date: 2016-04-27 / Esta tese apresenta uma análise do efeito das forças devido ao campo eletromagnético na deformação estrutural, estresses e fator de segurança em transformadores de potência quando estes são submetidos às correntes de energização ou correntes de inrush. A metodologia adotada baseia-se em uma avaliação magneto-mecânica do transformador através do método dos elementos finitos (MEF). Nesta perspectiva, a condição operacional de energização do transformador é considerada para estimar com precisão a densidade de campo magnético na estrutura ferromagnética deste e para encontrar na sequência os valores das tensões mecânicas ou forças nas direções axiais e radiais resultantes sobre os enrolamentos. Com este objetivo é implementado uma modelagem Bidimensional (2D) e tridimensional (3D) das estruturas discretizadas do transformador, em softwares consolidados em meios técnicos e acadêmicos, sendo estes baseados no Método de Elementos finitos, visando assim, a obtenção de resultados mais precisos no cálculo das variáveis descritas. São realizadas comparações entre os resultados provenientes do método numérico com aqueles obtidos via métodos analíticos, demonstrando que o MEF pode prever com mais precisão a distribuição dos estresses ao longo dos enrolamentos dos transformadores quando submetidos a condições limites de operação como as que ocorrem durante as correntes de inrush. São apresentados ainda resultados da densidade de fluxo magnético no transformador, mostrando que quando correntes elevadas circulam nos seus enrolamentos concêntricos, estas alteram o caminho do fluxo, provocando um acréscimo significativo do campo de dispersão e consequentemente das forças radiais e axiais. Com os resultados obtidos para o comportamento estrutural dos enrolamentos durante as correntes de inrush observou-se também que nos extremos dos enrolamentos, pontos onde se localizam os espaçadores, apresentam uma fragilidade estrutural maior devido às forças eletromagnéticas axiais. Este fato também implica em uma redução do fator de segurança nos extremos dos enrolamentos, o que deve ser considerado no projeto dos transformadores de potência. / This thesis presents an analysis of the effect of electromagnetic origin forces on structural deformation, stress and safety factor in power transformers when they are subjected to inrush currents. The methodology adopted is based on a magneto-mechanical assessment of the transformer using the finite element method (FEM). In this sense, the operating condition of its transformer energization is considered to accurately estimate the magnetic field density in the ferromagnetic structure and to find the values of mechanical stresses or forces in the axial and radial directions on the windings. These components are distributed over energized the high-voltage windings for observing the mechanical loading, which are more susceptible to such current actions. With this goal, it is implemented two- dimensional (2D) and threedimensional (3D) modeling of the discretized transformer structures in consolidated software, which are based on the Finite Elements Method, intended so to obtain more precise results in calculating the variables described. Comparisons between the results from the numerical method with those obtained by analytical methods are made, demonstrating that the FEM provides more precise distribution of stresses along the windings of the transformers when subjected to operating limits conditions as under currents inrush. It is also presented the magnetic flux distribution in the transformer, with high currents circulating in concentric winding of this. It modifies the flux path, causing in a significant increase in the leakage field and consequently on radial and axial forces. The results obtained for the structural behavior of the windings during inrush currents were also seen that the ends of the windings, where the spacers are located, producing high structural weakness due to the axial electromagnetic forces. This also implies a reduction in the safety factor at the ends windings ends and should be considered on the design of power transformers.

The UK Government has set an ambitious target to achieve 15% of final energy consumption from renewable sources by 2020. High Voltage Direct Current (HVDC) technology is an attractive solution for integrating offshore wind power farms farther from the coast. In the near future, more windfarms are likely to be connected to the UK grid using HVDC links. With the onset of this fairly new technology, new challenges are inevitable. This research is undertaken to help assist with these challenges by looking at possibilities of problems with respect to faster AC/DC interaction modes, especially, on the impact of inrush currents which occur during fault-recovery transients. In addition to that, possible mitigation strategies are also investigated. Initially, the relative merits of different transformer models are analysed with respect to inrush current transient studies. The most appropriate transformer model is selected and further validated using field measurement data. A detailed electro-magnetic-transient (EMT) model of a grid-connected MMC-HVDC system is prepared in PSCAD/EMTDC to capture the key dynamics of fault-recovery transformer inrush currents. It is shown that the transformer in an MMC system can evoke inrush currents during fault recovery, and cause transient interactions with the converter and the rest of the system, which should not be neglected. It is shown for the first time through a detailed dynamic analysis that if the current sensors of the inner-current control loops are placed at the converter-side of the transformer instead of the grid-side, the inrush currents will mainly flow from the grid and decay faster. This is suggested as a basic remedial action to protect the converter from inrush currents. Afterwards, analytical calculations of peak flux-linkage magnitude in each phase, following a voltage-sag recovery transient, are derived and verified. The effects of zero-sequence currents and fault resistance on the peak flux linkage magnitude are systematically explained. A zero-sequence-current suppression controller is also proposed. A detailed study is carried out to assess the key factors that affect the maximum peak flux-linkage and magnetisation-current magnitudes, especially with regard to fault specific factors such as fault inception angle, duration and fault-current attenuation. Subsequently, the relative merits of a prior-art inrush current mitigation strategy and its implementation challenges in a grid-connected MMC converter are analysed. It is shown that the feedforward based auxiliary flux-offset compensation scheme, as incorporated in the particular strategy, need to be modified with a feedback control technique, to alleviate the major drawbacks identified. Following that, eight different feedback based control schemes are devised, and a detailed dynamic and transient analysis is carried out to find the best control scheme. The relative merits of the identified control scheme and its implementation challenges in a MMC converter are also analysed. Finally, a detailed EMT model of an islanded MMC-HVDC system is implemented in PSCAD/EMTDC and the impacts of fault-recovery inrush currents are analysed. For that, initially, a MMC control scheme is devised in the synchronous reference frame and its controllers are systematically tuned. To obtain an improved performance, an equivalent control scheme is derived in the stationary reference frame with Proportional-Resonant controllers, and incorporated in the EMT model. Following that, two novel inrush current mitigation strategies are proposed, with the support of analytical equations, and verified.

My thesis is focused on realization of three inrush current limitors samples. This limiters will be used in ABB´s metal-clad, air-insulated switchgears for medium voltage distribution. On the basis of the results there is chosen the sample with optimal properties suitable for practice in the conclusion.

This thesis investigates the impact of resonant overvoltages and their origin. Series and parallel resonances are present in any electrical grid. The frequency of which this resonance occurs is called resonance frequency. For parallel resonance, which is mainly being studied in this thesis, a high impedance peak can be found at the resonance frequency. This impedance peak in conjunction with a harmonic rich current cause a kind of temporary overvoltages called resonant overvoltages. The harmonic content of the current is high following a fault clearing in the grid, due to transformer saturation. The resonance frequency is heavily dependent on the amount of reactance present in the grid, which entail that a change in reactance causes a change in the resonance frequency. The electromagnetic transient tool PSCAD has been used to investigate resonant overvoltages following transformer energization caused by faults and switching in Stockholm. Secondly, a model was created of a grid connecting off-shore wind power to the mainland via long AC submarine transmission cables. These cables, having a high capacitance, lower the resonance frequency. Faults in this model were simulated to investigate the phenomenon of resonant overvoltages in such a grid. This was especially interesting due to Swedens planned expansion of wind power in the Baltic sea. While resonant overvoltages were found in Stockholm they were not deemed significant due to their low magnitude and longevity. However, severe resonant overvoltages were found in the off-shore wind farm model. The worst resonant overvoltages had a maximum amplitude of the 2nd order harmonic voltage of 130 kV which, while eventually damped, were significant for up to 50 periods. Lastly, the phenomenon of an increased resonance frequency during the saturation of a transformer was studied. The most severe resonant overvoltages occured in a model where the frequency scans showed a resonance frequency of 98 Hz. Indicating, caution needs to be had during EMT-studies of resonant overvoltages while choosing what resonance frequency to study.

Nesta pesquisa, apresentam-se os principais eventos relacionados com a proteção de transformadores e sua correlação com os distúrbios de qualidade da energia elétrica (QEE). Neste sentido, foi desenvolvido um algoritmo que utiliza a transformada Wavelet (TW) e a lógica Fuzzy (LF) para classificar os eventos transitórios associados à proteção de transformadores. Estes eventos foram observados em um sistema elétrico de potência (SEP) simulado com a utilização do software Alternative Transients Program (ATP). Importa ressaltar que o sistema modelado apresenta transformadores ligados em paralelo, possibilitando o estudo de eventos decorrentes desta situação, como a energização solidária (Sympathetic Inrush). Por este SEP, modelado sobre parâmetros reais, foram simuladas várias situações transitórias, que provocam o aparecimento de correntes diferenciais, sendo estas direcionadas para análise do algoritmo desenvolvido. Afirma-se que, nos testes realizados, o algoritmo proposto apresentou um desempenho satisfatório perante as mais variadas situações a que foi submetido, identificando as causas das correntes diferenciais, sejam proporcionadas por defeitos ou por outras condições de operação aplicadas. / In this research, the main events related to the transformer protection and its correlation with the power quality disturbances (PQ) are presented. In this context, an algorithm based on Wavelet transform (WT) and Fuzzy logic (FL) was developed to classify the transient events associated with the transformer protection. These events were observed in an electrical power system (EPS) simulated using the Alternative Transients Program (ATP) software. It should be emphasized that the modeled system presents transformers connected in parallel, allowing the study of events of this situation, such as sympathetic inrush. For the simulated EPS, modeled based on real parameters, various transients situationswere simulated, causing the appearance of differentials currents which were directed to the analysis. The proposed algorithm showed a satisfactory performance tomany situations, identifying the causes of the differentials currents, either provided by faults or other operation conditions.