7 resultados para Generazione Distribuita Rinnovabili Controllo Tensione Smart Grid

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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In the developed world, grid-connected photovoltaics (PVs) are the fastest-growing segment of the energy market. From 1999 to 2009, this industry had a 42% compound annual growth-rate. From 2009 to 2013, it is expected to grow to 45%, and in 2013 the achievement of grid parity - when the cost of solar electricity becomes competitive with conventional retail (including taxes and charges) grid-supplied electricity - is expected in many places worldwide. Grid-connected PV is usually perceived as an energy technology for developed countries, whereas isolated, stand-alone PV is considered as more suited for applications in developing nations, where so many individuals still lack access to electricity. This rationale is based on the still high costs of PV when compared with conventional electricity. We make the case for grid-connected PV generation in Brazil, showing that with the declining costs of PV and the rising prices of conventional electricity, urban populations in Brazil will also enjoy grid parity in the present decade. We argue that governments in developing nations should act promptly and establish the mandates and necessary conditions for their energy industry to accumulate experience in grid-connected PV, and make the most of this benign technology in the near future. (C) 2010 Elsevier Ltd. All rights reserved.

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This paper proposes three new hybrid mechanisms for the scheduling of grid tasks, which integrate reactive and proactive approaches. They differ by the scheduler used to define the initial schedule of an application and by the scheduler used to reschedule the application. The mechanisms are compared to reactive and proactive mechanisms. Results show that hybrid approach produces performance close to that of the reactive mechanisms, but demanding less migrations.

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In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

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Fractures of the mandibular angle deserve particular attention because they represent the highest percentage of mandibular fractures and have the highest postsurgical complication rate, making them the most challenging and unpredictable mandibular fractures to treat. Despite the evolution in the treatment of maxillofacial trauma and fixation methods, no single treatment modality has been revealed to be ideal for mandibular angle fractures. Several methods of internal fixation have been studied with great variation in complications rates, especially postoperative infections. Recently, new studies have shown reduction of postsurgical complications rates using three-dimensional plates to treat mandibular angle fractures. Nevertheless, only few surgeons have used this type of plate for the treatment of mandibular angle fractures. The aim of this clinical report was to describe a case of a patient with a mandibular angle fracture treated by an intraoral approach and a three-dimensional rectangular grid miniplate with 4 holes, which was stabilized with monocortical screws. The authors show a follow-up of 8 months, without infection and with occlusal stability.

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The purpose of this article is to present a method which consists in the development of unit cell numerical models for smart composite materials with piezoelectric fibers made of PZT embedded in a non-piezoelectric matrix (epoxy resin). This method evaluates a globally homogeneous medium equivalent to the original composite, using a representative volume element (RVE). The suitable boundary conditions allow the simulation of all modes of the overall deformation arising from any arbitrary combination of mechanical and electrical loading. In the first instance, the unit cell is applied to predict the effective material coefficients of the transversely isotropic piezoelectric composite with circular cross section fibers. The numerical results are compared to other methods reported in the literature and also to results previously published, in order to evaluate the method proposal. In the second step, the method is applied to calculate the equivalent properties for smart composite materials with square cross section fibers. Results of comparison between different combinations of circular and square fiber geometries, observing the influence of the boundary conditions and arrangements are presented.

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Recently, researches have shown that the performance of metaheuristics can be affected by population initialization. Opposition-based Differential Evolution (ODE), Quasi-Oppositional Differential Evolution (QODE), and Uniform-Quasi-Opposition Differential Evolution (UQODE) are three state-of-the-art methods that improve the performance of the Differential Evolution algorithm based on population initialization and different search strategies. In a different approach to achieve similar results, this paper presents a technique to discover promising regions in a continuous search-space of an optimization problem. Using machine-learning techniques, the algorithm named Smart Sampling (SS) finds regions with high possibility of containing a global optimum. Next, a metaheuristic can be initialized inside each region to find that optimum. SS and DE were combined (originating the SSDE algorithm) to evaluate our approach, and experiments were conducted in the same set of benchmark functions used by ODE, QODE and UQODE authors. Results have shown that the total number of function evaluations required by DE to reach the global optimum can be significantly reduced and that the success rate improves if SS is employed first. Such results are also in consonance with results from the literature, stating the importance of an adequate starting population. Moreover, SS presents better efficacy to find initial populations of superior quality when compared to the other three algorithms that employ oppositional learning. Finally and most important, the SS performance in finding promising regions is independent of the employed metaheuristic with which SS is combined, making SS suitable to improve the performance of a large variety of optimization techniques. (C) 2012 Elsevier Inc. All rights reserved.

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The purpose of this article is to present a method which consists in the development of unit cell numerical models for smart composite materials with piezoelectric fibers made of PZT embedded in a non-piezoelectric matrix (epoxy resin). This method evaluates a globally homogeneous medium equivalent to the original composite, using a representative volume element (RVE). The suitable boundary conditions allow the simulation of all modes of the overall deformation arising from any arbitrary combination of mechanical and electrical loading. In the first instance, the unit cell is applied to predict the effective material coefficients of the transversely isotropic piezoelectric composite with circular cross section fibers. The numerical results are compared to other methods reported in the literature and also to results previously published, in order to evaluate the method proposal. In the second step, the method is applied to calculate the equivalent properties for smart composite materials with square cross section fibers. Results of comparison between different combinations of circular and square fiber geometries, observing the influence of the boundary conditions and arrangements are presented.