Teses em Engenharia Elétrica (Doutorado) - PPGEE/ITEC

URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/2317

O Doutorado Acadêmico inicio-se em 1998 e pertence ao Programa de Pós-Graduação em Engenharia Elétrica (PPGEE) do Instituto de Tecnologia (ITEC) da Universidade Federal do Pará (UFPA).

Navegar

Agora exibindo 1 - 11 de 11

Acesso aberto (Open Access)
Análise magnética e mecânica em transformadores sob correntes de energização e energização solidária
(Universidade Federal do Pará, 2019-10-01) LIMA, Diorge de Souza; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
The power transformer is one of the most important equipment in the electric power system, allowing the feasibility of connecting the generating centers to the consumer centers, even over long distances. Reliable and continuous operation is of fundamental importance for service maintenance and is subject to various types of disturbances that can lead to failures. In this perspective, studies of the dynamic behavior of transformer windings through computer simulations have been widely used to safely and accurately evaluate their operation. Therefore, this paper presents the methodology for research on a 50 MVA power transformer using the finite element method for static and time domain analysis. Thus, the study was performed by means of magnetic-mechanical couplings. In the first analysis (circuit study), the ATPDraw software was used to obtain the behavior of the inrush current and solidarity energization during the transformer bank energization. Therefore, in the ANSYS MAXWELL software magnetic studies were performed. For this, a real 3D model was used (taking into account the characteristics of the lamination core and windings, being in disc). Thus, the results of the behavior of magnetic induction and magnetic forces in the windings of the equipment are presented. Finally, in the ANSYS STRUCTURAL software, structural (mechanical) studies were performed. Also, as before, a close-to-real 3D model was used, presenting as results the behavior of the total deformation in the winding, the mechanical stress suffered and the degree of safety during the occurrence of energization. The static studies were considered three operating conditions: nominal condition, sympathetic inrush and inrush current. For the nominal condition, the equipment's plate data was used, for the energizing condition (sympathetic inrush and inrush current) the largest amplitude obtained during the simulation was used. It is noteworthy that for the time domain analysis, only the condition of the inrush current was analyzed, both for the high computational cost required and for being the worst condition in the static analysis.
Acesso aberto (Open Access)
Análise não paramétrica para identificação de fontes de distorções harmônicas em sistemas de energia elétrica: um estudo aplicado no campus universitário do Guamá da Universidade Federal do Pará
(Universidade Federal do Pará, 2016-02-19) MATOS, Edson Ortiz de; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
Nowadays, the use of non-linear loads and power electronics-based equipment in residential, commercial and industrial facilities are contributing to the significant increase of current harmonic distortion levels and, consequently voltage harmonic distortions, as noted in the Brazilian distribution systems. Increasing levels of harmonic distortion in electrical distribution networks is a concern to electric utilities and customers, because the presence of these harmonic sources causes, among others, loss of quality in the energy supply. With a focus on this problem, this thesis proposes the development of non-parametric regression models to identify and quantify what non-linear loads can be considered main sources of voltage harmonic distortion at a point of interest in the electric network. The proposed methodology is based on data correlation analysis, using non-parametric regression statistical models to establish the correlation among the non-linear loads harmonic currents and harmonic voltage at a point of interest. This model is built from harmonic voltage and currents measurements, obtained in measuring campaigns using power quality analyzers installed at the points of interest. In addition, it should be pointed out that these harmonic voltages and currents must be express in base units, rather than percent values in relation to the fundamental component, in order to prevent the influence in the creation of the regression model. An important aspect in this methodology is the use of techniques based on Kernel local polynomial regression, for the estimation of the regression model between harmonic voltage and current. To validate the models it is introduced the determination coefficient R2, which can be obtained from the Pearson correlation coefficient, to measure the accuracy degree of the developed models. The non-parametric regression procedure provides a great flexibility in the estimation of regression models, since it makes possible to carry out a more effective model fit to the data samples, and therefore it is able to characterize the influence of each harmonic source in more detail for the entire measurement period. This technique presented more reliable results and overcomes the shortcomings of the linear regression model, which requires the harmonic currents of other sources, called background, not to vary when analyzing a particular load current. The linear and non-parametric regression models were simulated using the program R, which is a language and environment for statistical calculations and graphs, and as test system it was used the Federal University of Pará electric distribution network, consisting of 84 (84) load busbars in 13.8 kV. The results so obtained are compared to those obtained with the linear regression models, and presented good performance, allowing its application for electric power distribution companies.
Acesso aberto (Open Access)
Detecção, classificação e quantificação automática de variações de tensão de curta duração para aplicação em análise de pós-operação em sistemas de energia elétrica
(Universidade Federal do Pará, 2006-05-19) MACHADO, Raimundo Nonato das Mercês; PELAES, Evaldo Gonçalves; http://lattes.cnpq.br/0255430734381362; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
The analysis of occurrences in electric power systems is of fundamental importance for secure operation of the system, and to maintain quality of the electric energy supplied to the consumers. The electric power utilities use equipments called disturbance registers (DR’s) for monitoring and diagnose of problems in the electric and protection systems. The waveforms usually analyzed in the electric power utilities operation centers, are those generated by events that usually cause the opening of lines due to circuitbreakers operation commanded by the protection devices. However, a great amount of stored data that can contain important information on the behavior and the performance of the system is not analyzed. The proposal of this work is to use the available data in electric power utilities control and operation centers obtained from DR’s equipments, to classify and quantify of automatic form signals that characterize power quality problems, such as, short duration voltage variations: sags, swells and interruptions. The proposed method uses wavelet transform to obtain a characteristic vector for voltages in phases A, B and C, and a probabilistic neural network is used for classification. The classified signals as presenting short-duration variation are quantified for duration and magnitude of the event, using the multiresolution decomposition signal analysis properties. Those parameters, then, will form a database where statistical procedures of analysis can be used to prepare reports regarding power quality features. The results obtained with the application of this proposed methodology to a real system are also presented.
Acesso aberto (Open Access)
Estimação das parcelas de contribuição de cargas não lineares na distorção harmônica de tensão de um barramento de interesse do sistema elétrico de potência utilizando rede neural artificial
(Universidade Federal do Pará, 2019-09-06) MANITO, Allan Rodrigo Arrifano; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
This work presents a methodology to estimate the non-linear loads contribution on voltage harmonic distortion at a bus of interest in the electric power system. The estimation process is carried out through the development of a model based on artificial neural networks (ANN) added to a sensitivity analysis in neural network input. The ANN model input is constituted by the non-linear loads harmonic currents considered in the studied system, and the ANN output corresponds to the harmonic voltage values in the bus under study, for the same harmonic frequency. The study is carried out for each harmonic order individually and the data required for the construction of the model as well as for the results validation have been obtained from synchronized measurement campaigns and by computational simulation, using harmonic load flow studies. Comparisons between reference results through computational simulation with the results obtained by neural model are carried out and it is observed that the developed methodology is able to classify correctly the impact of non-linear loads in the voltage distortion at a bus of interest of the electric system. Additionally, the effectiveness of the methodology is tested in two real systems in order to verify the good performance of this methodology considering real data obtained during measurement campaigns.
Acesso aberto (Open Access)
Estimador de estado harmônico trifásico incorporando Saturação de transformadores
(Universidade Federal do Pará, 2019-06-28) SOARES, Thiago Mota; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
Acesso aberto (Open Access)
Experimentos de mineração de dados aplicados a sistemas scada de usinas hidrelétricas
(Universidade Federal do Pará, 2012-04-13) OHANA, Ivaldo; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
The current model of the Brazilian electric sector allows equal terms to all actors and reduces the role of the State in this sector. This model forces the electrical utilities to improve the quality of their products and, as a prerequisite for this purpose, they should make more effective use of the enormous amount of operational data that are stored in databases, acquired from the operation of their electrical systems which use the hydroelectric power plants as their main source of energy generation. One of the main tools for managing the operation of these plants are the Supervisory Control and Data Acquisition systems (SCADA). Thus, the large amount of data stored in databases by SCADA systems, certainly containing relevant information, should be treated to discover relationships and patterns that would help in the understanding of many important operational aspects as well as in the evaluation of operational performance of the electric power systems. The process of Knowledge Discovery in Database (KDD) is the process of identification of patterns in large data sets, that are valid, new, and useful to improve the understanding of a problem or a decision-making procedure. Data Mining is the step within KDD that extracts useful information from large databases. In this scenario, the present study objective is to perform data mining experiments on data generated by power plants SCADA systems, to produce relevant information to assist in planning, operation, maintenance and security of hydro power plants and also contribute to the implementation of the culture of using data mining techniques applied to these plants.
Acesso aberto (Open Access)
Identificação de correntes de inrush na proteção diferencial de transformadores de potência através do gradiente da corrente diferencial e de mapas auto-organizáveis
(Universidade Federal do Pará, 2013-06-10) ALENCAR, Raidson Jenner Negreiros de; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
A principal dificuldade encontrada na proteção diferencial de transformadores de potência é a correta distinção entre as correntes de inrush e as correntes de faltas internas. Tradicionalmente os relés diferenciais executam esta tarefa utilizando a técnica de restrição por harmônicos baseada na premissa de que as correntes de inrush possuem alta concentração de componentes harmônicas de segunda ordem, contudo essa técnica nem sempre é eficaz. O presente trabalho tem como objetivo apresentar a proposta de duas novas metodologias capazes de realizar a identificação e distinção entre as correntes de inrush das correntes de faltas internas na proteção diferencial de transformadores de potência através de metodologias que não dependem do conteúdo de harmônicos do sinal da corrente diferencial. A primeira metodologia proposta, denominada de método do gradiente da corrente diferencial, é baseada no comportamento do vetor gradiente, obtido através da diferenciação numérica do sinal da corrente diferencial. O critério de distinção utilizado é baseado no desvio padrão do ângulo do vetor gradiente que apresenta comportamento diferenciado para correntes de inrush e correntes de curto-circuito. A segunda metodologia proposta é baseada na capacidade de reconhecimento e classificação de padrões das redes neurais de Mapeamento Auto-organizável de Kohonen. Como padrão de entrada e de treinamento da rede neural é utilizado um vetor contendo quatro níveis do espectro do desvio padrão do ângulo do vetor gradiente da corrente diferencial nas três fases do transformador de potência. A eficácia dos métodos foi testada através da simulação de diversas situações de faltas internas e correntes de inrush, incluindo situações de “Sympathetic Inrush”, em um transformador de potência usando o software EMTP/ATP e através da implementação do algoritmo em MATLAB®, apresentando resultados altamente promissores.
Desconhecido
Metodologia para compressão de sinais de energia elétrica a partir de registros de forma de onda utilizando algorítmos genéticos e redes neurais artificiais
(Universidade Federal do Pará, 2016-12-16) BARROS, Fabíola Graziela Noronha; NUNES, Marcus Vinícius Alves; http://lattes.cnpq.br/9533143193581447; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
This thesis proposes a methodology for compression of electrical power signals from waveform records in electric systems, using genetic algorithm (GA) and artificial neural network (ANN).The genetic algorithm is used to select and preserve the points that better characterize the waveform contoursA and the artificial neural network is used in the compression of other points as well as on the signal reconstruction process. Thus, the data resulting are formed by a part of the original signal and by a compressed complementary part in the form of synaptic weights. The proposed methodology selects and preserves a percentage of the original signal samples, which are aspects not explored in the literature. The method was tested using field data obtained from an oscillographic recorder installed in a 230kV electrical power system. The results presented compression rates ranging from 88.36 to 95.86 for preservation rates ranging from 2.5 to 10 , respectively.
Acesso aberto (Open Access)
Modelo matemático para otimização multiobjetivo do despacho econômico ambiental de usinas térmicas usando o NSGA-II
(Universidade Federal do Pará, 2017-07-14) MORAES, Nadime Mustafa; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
One of the priority tasks for thermoelectric plants is to supply the requested energy demand, ensuring the lowest possible cost. This task is more important in the Northern Region of Brazil, especially in the Industrial Hub of Manaus (PIM) and in the city itself, where a large part of this energy is supplied by Thermoelectric Power Plants (UTE). The selection of generators and their work regime is known as the Economic Dispatch (DE). The essential objective of ED is to operate UTEs by meeting demand at the lowest possible cost of fuel. However, the worldwide concern about pollution caused by fossil fuels in recent times to minimize fuel costs can not be considered the only objective to be achieved in the UTEs and limiting the emission of pollutants has become another primary objective. Thus, the Environmental Economic Dispatch (DEA) appears, which seeks not to reduce costs, but also emissions. To solve the optimization of this task there are several deterministic as well as heuristic methods. One of the most used methods according to the literature is the Genetic Algorithm of Non-dominated Classification, NSGA-II, considering two objective functions, a function of fuel cost and another quantity function. In this thesis, the proposed solution has the following contributions: it develops a new and unprecedented function to evaluate the environmental contamination produced by the UTEs that, in addition to minimizing the amount of pollutants, takes into account the influence of pollutants more harmful to the environment. This function, called the Emissions Index, is applied to the engines of two UTEs in the city of Manaus with satisfactory results. The Emissions Index and the traditional fuel cost function is optimized using the NSGA-II, determining optimal solutions for output power in several characteristic and non-characteristic scenarios of the plants, and can be applied to any thermoelectric plant. In order to analyze the viability of the solution proposed by this thesis, a set of ten thermal generating units of a UTE of the city of Manaus and the IEEE 118-bar System were used as case studies, demonstrating the robustness of the proposal in what refer to the solution presented. These results were significant considering the Emissions Index and using the optimization procedure of the non-dominated classification algorithm II (NSGA-II). This new DEA methodology enables specialists in the area to reduce costs and generate generation planning.
Acesso aberto (Open Access)
Otimização multiobjetivo da compensação de potência reativa em redes de distribuição considerando restrições de distorção harmônica
(Universidade Federal do Pará, 2014-11-14) AZEVEDO, Manoel Socorro Santos; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
The localization of capacitors banks in the electric power distribution networks, correctly sized, looks for to compensate eventual excesses of circulation of reactive power for transmission lines, what implies the reduction of operational costs for the reduction of the energy losses and an increase of the capacity of transmission of active power assuring the established levels of voltage and power factor simultaneously. The proliferation of the nonlinear loads produced a change in the scenarios of study of the electric power systems due to the degradation effects that the harmonic generated by them cause about the quality of the electric power. Considering this new scenario, this thesis has as general objective to develop a computational tool using computational intelligence supported in genetic algorithms (GA), for the multiobjective optimization of the reactive power compensation in distribution electric networks able to locate and size in a good way the necessary compensation units to achieve the best economic benefits and the maintenance of the indexes of quality of the energy settled down by the Brazilian norms. As technological innovation of the work, the developed computational tool allows to optimize the compensation of the reactive power to improve the power factor in polluted distribution networks with harmonics that, differently of previous methods, not alone it uses capacitors banks, but also harmonic filters with that objective. The NSGA-II algorithm is used to determine optimal solutions of Pareto for the problem and it allows the specialist to determine the most effective solutions. The formulation proposed in this thesis for the solution of the problem presents several novelties being able to highlight that the achieved solution allows to determine the compensation of reactive power in systems with certain harmonic penetration, complying with pertinent standards of power quality, with respect to the tolerated levels of harmonic distortion.
Desconhecido
Pré-despacho de carga em usinas termoelétricas considerando a gestão da manutenção via lógica fuzzy
(Universidade Federal do Pará, 2018-02-27) FONSECA JÚNIOR, Milton; BEZERRA, Ubiratan Holanda; http://lattes.cnpq.br/6542769654042813
This thesis presents a new proposal for load pre-dispatch considering the technical conditions of the engines of thermoelectric power plants by combining several maintenance and diagnostic techniques and using computational intelligence based on fuzzy logic. Diagnosis of the technical conditions of the engines is done using lubricant analysis, vibration analysis, and thermography. With this data and with the statistical analysis it is possible to predict when an engine can fail and consider this in the load pre-dispatch. To increase engine reliability and power supply, a Maintenance Management Program (MMP) is developed using management tools, applying only 4 TPM (Total Predictive Maintenance) pillars and combined them with predictive maintenance and diagnostics, thus allowing to reduce failures of plant equipment. Some results achieved after the implementation are: reduction of the annual cost of maintenance, reduction of corrective maintenance, increase of the MTBF (Mean Time Between Failures) and decrease of MTTR (Mean Time To Repair) in all areas. In addition, the proposed pre-dispatch scheme ensures the demanded power with a high degree of reliability and quality.

Navegar

Navegando Teses em Engenharia Elétrica (Doutorado) - PPGEE/ITEC por Orientadores "BEZERRA, Ubiratan Holanda"