933 resultados para Uncertainty in Wind Energy
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This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. 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 models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.
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Protein-energy malnutrition is a syndrome in which anaemia together with multivitamin and mineral deficiency may be present. The pathophysiological mechanisms involved have not, however, yet been completely elucidated. The aim of the present study was to evaluate the pathophysiological processes that occur in this anaemia in animals that were submitted to protein-energy malnutrition, in particular with respect to Fe concentration and the proliferative activity of haemopoietic cells. For this, histological, histochemical, cell culture and immunophenotyping techniques were used. Two-month-old male Swiss mice were submitted to protein-energy malnutrition with a low-protein diet (20g/kg) compared with control diet (400 g/kg). When the experimental group had attained a 20% loss of their original body weight, the animals from both groups received, intravenously, 20IU erythropoietin every other day for 14 d. Malnourished animals showed a decrease in red blood cells, Hb concentration and reticulocytopenia, as well as severe bone marrow and splenic atrophy. The results for serum Fe, total Fe-binding capacity, transferrin and erythropoietin in malnourished animals were no different from those of the control animals. Fe reserves in the spleen, liver and bone marrow were found to be greater in the malnourished animals. The mixed colony-forming unit assays revealed a smaller production of granulocyte-macrophage colony-forming units, erythroid burst-forming units, erythroid colony-forming units and CD45, CD117, CD119 and CD71 expression in the bone marrow and spleen cells of malnourished animals. These findings suggest that, in this protein-energy malnutrition model, anaemia is not caused by Fe deficiency or erythropoietin deficiency, but is a result of ineffective erythropoiesis.
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Inelasticity distributions in high-energy p-nucleus collisions are computed in the framework of the interacting gluon model, with the impact-parameter fluctuation included. A proper account of the peripheral events by this fluctuation has shown to be vital for the overall agreement with several reported data. The energy dependence is found to be weak.
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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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Incluye Bibliografía
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An important alteration of the equivalent loads profile has been observed in the electrical energy distribution systems, for the last years. Such fact is due to the significant increment of the electronic processors of electric energy that, in general, behave as nonlinear loads, generating harmonic distortions in the currents and voltages along the electric network. The effects of these nonlinear loads, even if they are concentrated in specific sections of the network, are present along the branch circuits, affecting the behavior of the entire electric network. For the evaluation of this phenomenon it is necessary the analysis of the harmonic currents flow and the understanding of the causes and effects of the consequent voltage harmonic distortions. The usual tools for calculation the harmonic flow consider one-line equivalent networks, balanced and symmetrical systems. Therefore, they are not tools appropriate for analysis of the operation and the influence/interaction of mitigation elements. In this context, this work proposes the development of a computational tool for the analysis of the three-phase harmonic propagation using Norton modified models and considering the real nature of unbalanced electric systems operation. © 2011 IEEE.
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Includes bibliography
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Each year, there is an increase in pesticide consumption and in its importance of use in the large-scale agricultural production, being fundamental the knowledge of application technology to the activity success. The objective of the present study was to evaluate the influence of working pressure on the drift generated by different spray nozzles, assessed in wind tunnel. The treatments were composed of two spray nozzles AXI 110015 and AXI 11002 with pressure levels of 276 and 414 kPa. The spray solution was composed by water and NaCl at 10%. The applications were conducted at wind speed of 2.0 m s-1, being the drift collected at 5.0; 10.0 and 15.0 m away from the spray boom and at heights of 0.2; 0.4; 0.6; 0.8 e 1.0 m from the tunnel floor. To both spray nozzles, the greatest drift was collected at the smallest distance to the spray-boom and at the lowest height. The AXI 11002 nozzle gave a smaller drift relative to the AXI 110015 nozzle for the two tested pressures and for all the collection points. Regardless of the nozzle, a rise in the working pressure increases the spray drift percentage at all distances in the wind tunnel.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.
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The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.
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We evaluate the potential for searching for isosinglet neutral heavy leptons (N), such as right-handed neutrinos, in the next generation of e+e- linear colliders, paying special attention to contributions from the reaction γe→WN initiated by photons from beamstrahlung and laser back-scattering. We find that these mechanisms are both competitive and complementary to the standard e+e-→vN annihilation process for producing neutral heavy leptons in these machines and greatly extends the search range over HERA and LEP200.
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Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.