164 resultados para Test systems


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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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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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This letter presents an alternative approach for reducing the total real power losses by using a continuation method. Results for two simple test systems and for the IEEE 57-bus system show that this procedure results in larger voltage stability margin. Besides, the reduction of real power losses obtained with this procedure leads to significant money savings and, simultaneously, to voltage profile improvement. Comparison between the solution of an optimal power flow and the proposed method shows that the latter can provide near optimal results and so, it can be a reasonable alternative to power system voltage stability enhancement.

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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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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

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This work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

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The Glutatione-S-transferases (GSTs) comprise a family of enzymes closely associated with the cell detoxification of xenobiotics. GSTs exist as homo- or heterodimers and have been grouped into at least seven distinct classes. The main function of GSTs is to catalyze the conjugation of reduced glutathione (GSH) to an electrophilic site of a broad range of potentially toxic and carcinogenic compounds, thereby making such compounds less dangerous and enabling their ready-excretion. Placental GST, known as GST-P 7-7, is the main isoform found in normal placental tissue and comprises 67% of the total GST concentration in this tissue. During development, GST-P 7-7 decreases in concentration and is absent in adult tissues. Interestingly, GST-P 7-7 expression has been detected in adult tissues after exposure to carcinogenic agents in several experimental test systems, being considered a reliable biomarker of exposure and susceptibility in early phases of carcinogenesis. In this article, we review a series of studies involving GST-P 7-7 expression as a suitable tool for understanding cancer pathogenesis, especially cancer risk.

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Groundwater contamination with benzene, toluene, ethylbenzene and xylene (BTEX) has been increasing, thus requiring an urgent development of methodologies that are able to remove or minimize the damages these compounds can cause to the environment. The biodegradation process using microorganisms has been regarded as an efficient technology to treat places contaminated with hydrocarbons, since they are able to biotransform and/or biodegrade target pollutants. To prove the efficiency of this process, besides chemical analysis, the use of biological assessments has been indicated. This work identified and selected BTEX-biodegrading microorganisms present in effluents from petroleum refinery, and evaluated the efficiency of microorganism biodegradation process for reducing genotoxic and mutagenic BTEX damage through two test-systems: Allium cepa and hepatoma tissue culture (HTC) cells. Five different non-biodegraded BTEX concentrations were evaluated in relation to biodegraded concentrations. The biodegradation process was performed in a BOO Trak Apparatus (HACH) for 20 days, using microorganisms pre-selected through enrichment. Although the biodegradation usually occurs by a consortium of different microorganisms, the consortium in this study was composed exclusively of five bacteria species and the bacteria Pseudomonas putida was held responsible for the BTEX biodegradation. The chemical analyses showed that BTEX was reduced in the biodegraded concentrations. The results obtained with genotoxicity assays, carried out with both A. cepa and HTC cells, showed that the biodegradation process was able to decrease the genotoxic damages of BTEX. By mutagenic tests, we observed a decrease in damage only to the A. cepa organism. Although no decrease in mutagenicity was observed for HTC cells, no increase of this effect after the biodegradation process was observed either. The application of pre-selected bacteria in biodegradation processes can represent a reliable and effective tool in the treatment of water contaminated with BTEX mixture. Therefore, the raw petroleum refinery effluent might be a source of hydrocarbon-biodegrading microorganisms. (c) 2010 Elsevier B.A. All rights reserved.

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The conventional power flow method is considered to be inadequate to obtain the maximum loading point because of the singularity of Jacobian matrix. Continuation methods are efficient tools for solving this kind of problem since different parameterization schemes can be used to avoid such ill-conditioning problems. This paper presents the details of new schemes for the parameterization step of the continuation power flow method. The new parameterization options are based on physical parameters, namely, the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, and transmission line power losses (real and reactive). The simulation results obtained with the new approach for the IEEE test systems (14, 30, 57, and 118 buses) are presented and discussed in the companion paper. The results show that the characteristics of the conventional method are not only preserved but also improved.

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New parameterization schemes have been proposed by the authors in Part I of this paper. In this part these new options for the parameterization of power flow equations are tested, namely, the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, and the transmission line power losses (real and reactive). These different parameterization schemes can be used to obtain the maximum loading point without ill-conditioning problems, once the singularity of Jacobian matrix is avoided. The results obtained with the new approach for the IEEE test systems (14, 30, 57, and 118 buses) show that the characteristics of the conventional method are not only preserved but also improved. In addition, it is shown that the proposed method and the conventional one can be switched during the tracing of PV curves to determine, with few iterations, all points of the PV curve. Several tests were also carried out to compare the performance of the proposed parameterization schemes for the continuation power flow method with the use of both the secant and tangent predictors.

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A method for optimal transmission network expansion planning is presented. The transmission network is modelled as a transportation network. The problem is solved using hierarchical Benders decomposition in which the problem is decomposed into master and slave subproblems. The master subproblem models the investment decisions and is solved using a branch-and-bound algorithm. The slave subproblem models the network operation and is solved using a specialised linear program. Several alternative implementations of the branch-and-bound algorithm have been rested. Special characteristics of the transmission expansion problem have been taken into consideration in these implementations. The methods have been tested on various test systems available in the literature.

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This paper applies two methods of mathematical decomposition to carry out an optimal reactive power flow (ORPF) in a coordinated decentralized way in the context of an interconnected multi-area power system. The first method is based on an augmented Lagrangian approach using the auxiliary problem principle (APP). The second method uses a decomposition technique based on the Karush-Kuhn-Tucker (KKT) first-order optimality conditions. The viability of each method to be used in the decomposition of multi-area ORPF is studied and the corresponding mathematical models are presented. The IEEE RTS-96, the IEEE 118-bus test systems and a 9-bus didactic system are used in order to show the operation and effectiveness of the decomposition methods.

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In this work the multiarea optimal power flow (OPF) problem is decoupled into areas creating a set of regional OPF subproblems. The objective is to solve the optimal dispatch of active and reactive power for a determined area, without interfering in the neighboring areas. The regional OPF subproblems are modeled as a large-scale nonlinear constrained optimization problem, with both continuous and discrete variables. Constraints violated are handled as objective functions of the problem. In this way the original problem is converted to a multiobjective optimization problem, and a specifically-designed multiobjective evolutionary algorithm is proposed for solving the regional OPF subproblems. The proposed approach has been examined and tested on the RTS-96 and IEEE 354-bus test systems. Good quality suboptimal solutions were obtained, proving the effectiveness and robustness of the proposed approach. ©2009 IEEE.