910 resultados para content distribution networks
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An analysis of the performances of three important methods for generators and loads loss allocation is presented. The discussed methods are: based on pro-rata technique; based on the incremental technique; and based on matrices of circuit. The algorithms are tested considering different generation conditions, using a known electric power system: IEEE 14 bus. Presented and discussed results verify: the location and the magnitude of generators and loads; the possibility to have agents well or poorly located in each network configuration; the discriminatory behavior considering variations in the power flow in the transmission lines. © 2004 IEEE.
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In order to evaluate the bean yield under different water table levels as well as the moisture and nitrate distribution in the soil profile, a field experiment was carried out at the experimental area from the College of Agronomic Sciences - UNESP, Botucatu, SP, Brazil. Beans were grown in field lysimeters and subjected to five water table depths:30; 40; 50; 60 and 70 cm. The moisture in the soil profile was gravimetrically determined through samples obtained at 10; 20; 30; 40; 50; 60 and 70cm of depth. The water table depths of 30cm and 40cm showed the highest productivities (3,228.4 kg.ha-1 and 3,422.1 kg.ha-1, respectively), showing no statistical differences between each other. The highest productivity was related to the two most elevated water table levels (30 and 40cm), which provided the highest moisture average values on basis of volume in the soil profile (33.3 e 31%) as well as the consumptive use of water (416 and 396 mm). The nitrate content during the bean cycle at the extraction depth of 60cm has been under the safe drinking limit of 10 mg.1-1 for water table depths of 30; 40; 50 and 60cm, showing the denitrification effectiveness as a way of controlling water table from nitrate pollution. The water table handling allowed the attainment of high bean productivity levels, as well as the reduction of the nitrate level.
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The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder. © 2006 IEEE.
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The structure and ultrastructure of immature to fully mature glandular dots in the leaf, floral organs and fruit, and their secretion components were described in Caesalpinia echinata Lam. (Leguminosae) for the first time. Data showed that glandular dots were groups of idioblasts with contents that reacted positively for both lipophilic and hydrophilic substances. Idioblasts originated from successive divisions of the ground meristem cells or mesophyll cells of an ovary of a fertilized flower. Following division, cells enlarged, the cytoplasm became denser and its content became full. No idioblasts were observed after fruit sclerification. Besides these mixed-content idioblasts, some cells in the sepals, petals and mesocarp were found to contain phenolic compounds, which probably represent a kind of constitutive defense mechanism, once the flowers and fruits become highly fitness-valued parts of the plant and can be commonly attacked. The contents of the idioblasts are released as the growth rate of the embryo increases, indicating that the plant probably diverts the precursors of secondary metabolites into the primary metabolism, at this critical time of embryo development.
Resumo:
In order to evaluate the bean yield under different water table levels as well as the moisture and nitrate distribution in the soil profile, a field experiment was carried out in the experimental area of the College of Agricultural Sciences - UNESP, Botucatu, SP, Brazil. Beans were grown in field lysimeters under five water table depths: 30; 40; 50; 60 and 70 cm. The moisture in the soil profile was determined gravimetrically using samples collected at 10; 20; 30; 40; 50; 60 and 70 cm deep. The water table depths of 30cm and 40cm showed the highest productivities (3,228.4kg.ha-1 and 3,422.1kg.ha-1, respectively), with no statistical differences between them. The highest productivity was related to the two highest water table levels (30 and 40cm), which provided the highest moisture average values on the basis of volume in the soil profile (33.3 e 31%) as well as the consumptive use of water (416 and 396mm). The nitrate content during the bean cycle at the extraction depth of 60cm was below the safe drinking limit of 10mg.1-1 for water table depths of 30; 40; 50 and 60cm, which shows the denitrification efficiency as a way of controlling nitrate pollution in water tables. The management of water table can lead to high levels of bean yield and to a better control of nitrate pollution in underground water.
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The use of sensorless technologies is an increasing tendency on industrial drivers for electrical machines. The estimation of electrical and mechanical parameters involved with the electrical machine control is used very frequently in order to avoid measurement of all variables related to this process. The cost reduction may also be considered in industrial drivers, besides the increasing robustness of the system, as an advantage of the use of sensorless technologies. This work proposes the use of a recurrent artificial neural network to estimate the speed of induction motor for sensorless control schemes using one single current sensor. Simulation and experimental results are presented to validate the proposed approach. ©2008 IEEE.
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An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining an excellent quality solution for this problem is presented. In each step of the CHA, a sensitivity index is used to add a circuit or a substation to the distribution network. This sensitivity index is obtained solving the DNP problem considering the numbers of circuits and substations to be added as continuous variables (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an efficient nonlinear optimization solver. A local improvement phase and a branching technique were implemented in the CHA. Results of two tests using a distribution network are presented in the paper in order to show the ability of the proposed algorithm. ©2009 IEEE.
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An alternative method is presented in this paper to identify the harmonic components of non-linear loads in single phase power systems based on artificial neural networks. The components are identified by analyzing the single phase current waveform in time domain in half-cycle of the ac voltage source. The proposed method is compared to the fast Fourier transform. Simulation and experimental results are presented to validate the proposed approach.
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In an evermore competitive environment, power distribution companies need to continuously monitor and improve the reliability indices of their systems. The network reconfiguration (NR) of a distribution system is a technique that well adapts to this new deregulated environment for it allows improvement of system reliability indices without the onus involved in procuring new equipment. This paper presents a reliability-based NR methodology that uses metaheuristic techniques to search for the optimal network configuration. Three metaheuristics, i.e. Tabu Search, Evolution Strategy, and Differential Evolution, are tested using a Brazilian distribution network and the results are discussed. © 2009 IEEE.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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This work proposes a methodology for optimized allocation of switches for automatic load transfer in distribution systems in order to improve the reliability indexes by restoring such systems which present voltage classes of 23 to 35 kV and radial topology. The automatic switches must be allocated on the system in order to transfer load remotely among the sources at the substations. The problem of switch allocation is formulated as nonlinear constrained mixed integer programming model subject to a set of economical and physical constraints. A dedicated Tabu Search (TS) algorithm is proposed to solve this model. The proposed methodology is tested for a large real-life distribution system. © 2011 IEEE.
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The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.
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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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This paper presents a mixed-integer linear programming approach to solving the optimal fixed/switched capacitors allocation (OCA) problem in radial distribution systems with distributed generation. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. © 2011 IEEE.
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Includes bibliography