952 resultados para direct current (dc) model


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A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed integer nonlinear programming (MINLP) problem, and in this approach, the so-called fathoming tests in the B&B algorithm were redefined and a nonlinear programming (NLP) problem is solved in each node of the B& B tree, using an interior-point method. Pseudocosts were used to manage the development of the B&B tree and to decrease its size and the processing time. There is no guarantee of convergence towards global optimisation for the MINLP problem. However, preliminary tests show that the algorithm easily converges towards the best-known solutions or to the optimal solutions for all the tested systems neglecting the electrical losses. When the electrical losses are taken into account, the solution obtained using the Garver system is better than the best one known in the literature.

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This study investigated the effects of electrolytic treatment using Dimensionally Stable Anode (DSA, 70%TiO2/30%RuO2) type electrodes in simulated wastewater containing aromatic amine n-phenyl-n'-1,3-dimethylbutyl-p-phenylenediamine (Flexzone 7P). A low direct current density of 0.025 A cm(-2) was applied for periods up to 60 minutes and a 52.6% decrease in Flexzone 7P concentration was observed. Ultraviolet-visible spectra, gas chromatography, toxicity and biodegradation tests were carried out with the aim of verifying the toxic by-products that were formed. Ultraviolet-visible spectra of simulated wastewater exhibited changes in the aromatic amine's molecular structure. Additionally, based on the S. cerevisiae toxicity test, it was observed that detoxification of the wastewater occurred after 15 minutes of electrolysis. It was also observed that five minutes of treatment were sufficient to improve the biodegradation rate, determined through the respirometric Bartha method.

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The aim of this work is to propose a flow spectrophotometric procedure for manganese determination in steel based on electrochemical oxidation of Mn(II) to Mn(VII) at a Pt electrode surface by means of the catalytic effect of Ag(I). The on-line oxidation step was obtained by injecting sample and electrolyte solution directly into an electrolytic cell. After electrolysis, the injectate was homogenized by bubbling air. The permanganate ions produced were passed through the spectrophotometer where absorbance was monitored at 545 nm. Effects of direct current, silver concentration, timing, flow rates, concentration and composition of support electrolyte were investigated. Direct current and silver content manifested themselves as the most relevant parameters. For determination of manganese in the 5.00 - 150 mg L -1 range (r=0,9998) and 60 s electrolysis time, the sample throughput was 20 h -1. Accuracy was assessed by analyzing ten steel standard reference materials. Results are precise (R.S.D. <3%) and in agreement with certified values of reference materials and with standard methods at 95% confidence level.

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This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.

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This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.

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This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering open access. The methodology finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with multiples generation scenarios. The model presented is solved using a specialized genetic algorithm. The methodology is tested in a system from the literature. ©2008 IEEE.

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Transmission expansion planning (TEP) is a non-convex optimization problem that can be solved via different heuristic algorithms. A variety of classical as well as heuristic algorithms in literature are addressed to solve TEP problem. In this paper a modified constructive heuristic algorithm (CHA) is proposed for solving such a crucial problem. Most of research papers handle TEP problem by linearization of the non-linear mathematical model while in this research TEP problem is solved via CHA using non-linear model. The proposed methodology is based upon Garver's algorithm capable of applying to a DC model. Simulation studies and tests results on the well known transmission network such as: Garver and IEEE 24-bus systems are carried out to show the significant performance as well as the effectiveness of the proposed algorithm. © 2011 IEEE.

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This paper presents a novel mathematical model for the transmission network expansion planning problem. Main idea is to consider phase-shifter (PS) transformers as a new element of the transmission system expansion together with other traditional components such as transmission lines and conventional transformers. In this way, PS are added in order to redistribute active power flows in the system and, consequently, to diminish the total investment costs due to new transmission lines. Proposed mathematical model presents the structure of a mixed-integer nonlinear programming (MINLP) problem and is based on the standard DC model. In this paper, there is also applied a specialized genetic algorithm aimed at optimizing the allocation of candidate components in the network. Results obtained from computational simulations carried out with IEEE-24 bus system show an outstanding performance of the proposed methodology and model, indicating the technical viability of using these nonconventional devices during the planning process. Copyright © 2012 Celso T. Miasaki et al.

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To become competitive, ultimately, photovoltaics should have its costs reduced and use photovoltaic systems of greater efficiency. The main steps in this direction are the use of new materials, the improvement in the manufacture of modules and the adoption of techniques of maximum power point tracking and of solar tracking. This article aims at presenting the project and development of an azimuth and elevation solar tracker, based on a new conception of the positioning sensor, composed of an array of four photoresistors. The two direct current motors that operate in the vertical and horizontal axes are controlled by a proportional-integral microcontroller. The conditions of the project were low cost, small energy consumption and versatility. The microcontroller can also incorporate a maximum power point tracking algorithm. The performance of solar tracker prototype in the initial phase of field tests can be considered appropriate. © Institution of Engineers Australia, 2013.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Televisão Digital: Informação e Conhecimento - FAAC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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