An efficient neural approach to economic load dispatch in power systems

A neural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper, Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements the ability of neural networks to realize some complex nonlinear function makes them attractive for system optimization the neural networks applyed in economic load dispatch reported in literature sometimes fail to converge towards feasible equilibrium points the internal parameters of the modified Hopfield network developed here are computed using the valid-subspace technique These parameters guarantee the network convergence to feasible quilibrium points, A solution for the economic load dispatch problem corresponds to an equilibrium point of the network. Simulation results and comparative analysis in relation to other neural approaches are presented to illustrate efficiency of the proposed approach.

Study of the timber constructive systems that are more commercialized in Brazil

The Brazilian houses in wood are executed with several techniques and species, in function of the areas they are located, therefore, it is treated of regional traditional houses, built practically without modem technological resources. These houses are the ones of the tropical areas, where there is abundance of this material, or the ones of the south region, prevailing the European immigrant's constructive techniques. Nowadays, in the urbanized centers of the country it is observed that this type of house can be found sheltering the most lacking populations, in the slums; or in highly sophisticated residential units which are conceived and executed by specialist professionals for a social class of high purchasing power; or still, those that are marketed by companies of small load, that offer standardized residences, usually acquired by the middle class as second residence, in the field or in the coast. The work has for objective to study the houses of these companies that are consolidated at the market, identifying the constructive system, the product; as well as, its production process, trying to verify which technologies are incorporated to these processes. The analysis that was made allows a larger understanding of the product, wood house, that exists in the market and identification of the technological degree in the productive process of those constructive systems.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

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

Optimal Frequency Range Selection for PZT Transducers in Impedance-Based SHM Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Strategic capacitor placement in distribution systems by minimisation of harmonics amplification because of resonance

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

Primary power distribution systems planning taking into account reliability, operation and expansion costs

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Robust State-Derivative Feedback LMI-Based Designs for Linear Descriptor Systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Dynamic Tracking with Zero Variation and Disturbance Rejection Applied to Discrete-Time Systems

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

Less Conservative Control Design for Linear Systems with Polytopic Uncertainties via State-Derivative Feedback

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Chemical attributes of a savannah Typic Hapludox soil under management systems

O trabalho teve por objetivo estudar as modificações de atributos químicos de um Latossolo Vermelho após dois anos de manejo com adubação orgânica e/ou mineral com diferentes sistemas de cultivo. O experimento foi realizado na área experimental da Universidade Estadual Paulista - UNESP, localizada no município de Selvíria, Estado do Mato Grosso do Sul, no ano agrícola 2004/2005 e 2005/2006. Os tratamentos foram: cultivo convencional; cultivo mínimo e semeadura direta. As adubações foram: testemunha (sem adubação); adubação mineral (300 kg ha-1 da fórmula 20-00-20); adubação orgânica (esterco bovino - 20 Mg ha-1); adubação orgânica (esterco bovino) + ½ adubação mineral recomendada para a cultura utilizada; 20 e 30 Mg ha-1 de lodo de esgoto. em um ano foi utilizada a soja como cultura e no seguinte o sorgo. Avaliaram-se os atributos químicos do solo em quatro camadas. Os atributos químicos do Latossolo Vermelho foram modificados no primeiro ano após as adubações; a adubação com esterco, lodo de esgoto e a combinação do esterco+adubação mineral foram eficazes em modificar os atributos químicos do solo estudado; o lodo de esgoto foi mais eficaz na recuperação do P do solo e, a semeadura direta contribuiu para o aumento de K no solo

Model for determining flow diameter and economic velocity in water elevating systems

The purpose of this paper was to develop a model for calculating the economical flow diameter and velocity, by obtaining the economical diameter, using Swamee's friction factor equation, by minimizing the total annual cost. The application of the model to a regular supply condition showed that the diameter of the actual condition, 250 mm, compared with the diameter calculated by the mode, at the same tariff as that applied to the property ( ground), 284.1 mm, involved the necessity to generate, transmit, and distribute extra electrical energy, due to the higher load loss caused by the original diameter, approximately 30800 kWh/year. This means that in one year, the consumer would spend R$2,804.00 more on pumping cost alone.

The effect of sodium chloride on the formation of W/O microemulsions in soy bean oil/surfactant/water systems and the solubilization of small hydrophilic molecules

Partial pseudoternary phase diagrams were constructed for soy bean oil (SBO)/surfactant/NaCl aqueous solution systems, at 25 degrees C, using the anionic sodium bis(2-ethylhexyl) sulfosuccinate (ACT) and zwiterionic phosphatidylcholine (PC) or mixtures of these surfactants. The isotropic single phase of water-in-oil (W/O) microemulsions (MEs) is shown in the phase diagram and their viscosity reported. ME samples containing small amount of surfactant exhibit slightly higher viscosity than pure SBO, and were used in the solubilization of small water soluble molecules. NaCl enhances the area of the ME phase and MEs with different surfactant composition exhibit different induction time as obtained from tests of oxidative stability, and so are the MEs enriched with ascorbic acid, folic acid and FeSO4, with the latter exhibiting lower stability. The so prepared enriched soy bean oil has potential application in food industry since the surfactants are food grade. (C) 2007 Elsevier B.V. All rights reserved.

Artificial immune systems for classification of petroleum well drilling operations

This paper presents two approaches of Artificial Immune System for Pattern Recognition (CLONALG and Parallel AIRS2) to classify automatically the well drilling operation stages. The classification is carried out through the analysis of some mud-logging parameters. In order to validate the performance of AIS techniques, the results were compared with others classification methods: neural network, support vector machine and lazy learning.