959 resultados para Distribution power systems restoration


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The power system stabilizers are used to suppress low-frequency electromechanical oscillations and improve the synchronous generator stability limits. This master thesis proposes a wavelet-based power system stabilizer, composed of a new methodology for extraction and compensation of electromechanical oscillations in electrical power systems based on the scaling coefficient energy of the maximal overlap discrete wavelet transform in order to reduce the effects of delay and attenuation of conventional power system stabilizers. Moreover, the wavelet coefficient energy is used for electric oscillation detection and triggering the power system stabilizer only in fault situations. The performance of the proposed power system stabilizer was assessed with experimental results and comparison with the conventional power system stabilizer. Furthermore, the effects of the mother wavelet were also evaluated in this work

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The progressing cavity pumping (PCP) is one of the most applied oil lift methods nowadays in oil extraction due to its ability to pump heavy and high gas fraction flows. The computational modeling of PCPs appears as a tool to help experiments with the pump and therefore, obtain precisely the pump operational variables, contributing to pump s project and field operation otimization in the respectively situation. A computational model for multiphase flow inside a metallic stator PCP which consider the relative motion between rotor and stator was developed in the present work. In such model, the gas-liquid bubbly flow pattern was considered, which is a very common situation in practice. The Eulerian-Eulerian approach, considering the homogeneous and inhomogeneous models, was employed and gas was treated taking into account an ideal gas state. The effects of the different gas volume fractions in pump volumetric eficiency, pressure distribution, power, slippage flow rate and volumetric flow rate were analyzed. The results shown that the developed model is capable of reproducing pump dynamic behaviour under the multiphase flow conditions early performed in experimental works

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Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper deals with approaches for sparse matrix substitutions using vector processing. Many publications have used the W-matrix method to solve the forward/backward substitutions on vector computer. Recently a different approach has been presented using dependency-based substitution algorithm (DBSA). In this paper the focus is on new algorithms able to explore the sparsity of the vectors. The efficiency is tested using linear systems from power systems with 118, 320, 725 and 1729 buses. The tests were performed on a CRAY Y MP2E/232. The speedups for a fast-forward/fast-backward using a 1729-bus system are near 19 and 14 for real and complex arithmetic operations, respectively. When forward/backward is employed the speedups are about 8 and 6 to perform the same simulations.

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This article presents a well-known interior point method (IPM) used to solve problems of linear programming that appear as sub-problems in the solution of the long-term transmission network expansion planning problem. The linear programming problem appears when the transportation model is used, and when there is the intention to solve the planning problem using a constructive heuristic algorithm (CHA), ora branch-and-bound algorithm. This paper shows the application of the IPM in a CHA. A good performance of the IPM was obtained, and then it can be used as tool inside algorithm, used to solve the planning problem. Illustrative tests are shown, using electrical systems known in the specialized literature. (C) 2005 Elsevier B.V. All rights reserved.

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This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

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This work proposes a methodology to generalize the Y-connections for 12- and 18-pulse autotransformers. A single mathematical expression, obtained through simple trigonometric operations, represents all the connections. The proposed methodology allows choosing any ratio between the input and the output voltages. The converters can operate either as step-up or as step-down voltage. To simplify the design of the windings, graphics are generated to calculate the turn-ratio and the polarity of each secondary winding, with respect to the primary winding. A design example, followed by digital simulations, illustrates the presented steps. Experimental results of two prototypes (12 and 18 pulses) are presented. The results also show that high power factor is an inherent characteristic of multi-pulse converters, without any active or passive power factor pre-regulators needs. (c) 2005 Elsevier B.V. All rights reserved.

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O método de fluxo de carga convencional é considerado inadequado para se obter o ponto de máximo carregamento (PMC) de sistemas de potência, devido à singularidade da matriz Jacobiana neste ponto. Os métodos da continuação são ferramentas eficientes para a solução deste tipo de problema, visto que técnicas de parametrização podem ser utilizadas para evitar a singularidade da matriz Jacobiana. Neste trabalho, novas opções para a etapa de parametrização do método da continuação são apresentadas. Mostra-se que variáveis com claro significado físico podem ser utilizadas na etapa de parametrização. As seguintes variáveis foram testadas: perda total de potência ativa e reativa, potência ativa e reativa na barra de referência, potência reativa das barras de geração, e as perdas de potência ativa e reativa nas linhas de transmissão (LT). Além de facilitar a implementação computacional do método de continuação, as técnicas de parametrização apresentadas simplificam a definição matemática e o entendimento do método por parte de engenheiros de potência, visto que os métodos de continuação existentes na literatura sempre utilizam técnicas de parametrização complexas, e de interpretação puramente geométrica. Resultados obtidos com a nova metodologia para os sistemas testes do IEEE (14, 30, 57 e 118 barras) mostram que as características de convergência do método de fluxo de carga convencional são melhoradas na região do PMC. Além disso, durante o traçado das curvas PV, as diversas técnicas de parametrização podem ser comutadas entre si possibilitando o cálculo de todos os pontos da curva com um número reduzido de iterações. Diversos testes são realizados para proporcionar a comparação do desempenho dos esquemas de parametrização propostos.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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