Location and contract pricing of distributed generation using a genetic algorithm

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelo de otimização para seleção de árvores matrizes de Eucalyptus grandis

Individual data of basic density and volume of wood, pulp kappa number, soluble lignin, cost of pulping process as well as gravimetric gross yield of pulping process were used from 64 trees of Eucalyptus grandis W. Hill ex Maiden from a commercial population at Lençóis Paulista, SP. The Eucalyptus grandis's seeds were originally from a Seed Production Area (SPA) of Duratex S/A at Botucatu, SP. Obtained data were quantified considering objective of maximization no-bleaching pulp and volume and mass wood restriction, mass of residual and soluble lignin, planted area and pulping process cost. it has also been aimed a selection method for matrix trees through mathematical programming techniques. Obtained strategy maximized the economical result, selected matrix trees and followed all limits of technological and organizing productivities imposed by the company. It also aimed the production of no-bleaching pulp within the planned time.

Placement and sizing evaluation of distributed generation in electric power systems

This paper presents a methodology for the placement and sizing evaluation of distributed generation (DG) in electric power systems. The candidate locations for DG placement are identified on the bases of Locational Marginal Prices (LMP's) obtained from an optimal power flow solution. The problem is formulated for two different objectives: social welfare maximization and profit maximization. For each DG unit an optimal placement is identified for each of the objectives.

Optimal allocation of distributed generators providing reactive power support ancillary service

Problems as voltage increase at the end of a feeder, demand supply unbalance in a fault condition, power quality decline, increase of power losses, and reduction of reliability levels may occur if Distributed Generators (DGs) are not properly allocated. For this reason, researchers have been employed several solution techniques to solve the problem of optimal allocation of DGs. This work is focused on the ancillary service of reactive power support provided by DGs. The main objective is to price this service by determining the costs in which a DG incurs when it loses sales opportunity of active power, i.e, by determining the Loss of Opportunity Costs (LOC). The LOC will be determined for different allocation alternatives of DGs as a result of a multi-objective optimization process, aiming the minimization of losses in the lines of the system and costs of active power generation from DGs, and the maximization of the static voltage stability margin of the system. The effectiveness of the proposed methodology in improving the goals outlined was demonstrated using the IEEE 34 bus distribution test feeder with two DGs cosidered to be allocated. © 2011 IEEE.

A multi-objective evaluation of the impact of the penetration of Distributed Generation

This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Genetic diversity of the HLA-G coding region in Amerindian populations from the Brazilian Amazon: a possible role of natural selection

HLA-G has an important role in the modulation of the maternal immune system during pregnancy, and evidence that balancing selection acts in the promoter and 3′UTR regions has been previously reported. To determine whether selection acts on the HLA-G coding region in the Amazon Rainforest, exons 2, 3 and 4 were analyzed in a sample of 142 Amerindians from nine villages of five isolated tribes that inhabit the Central Amazon. Six previously described single-nucleotide polymorphisms (SNPs) were identified and the Expectation-Maximization (EM) and PHASE algorithms were used to computationally reconstruct SNP haplotypes (HLA-G alleles). A new HLA-G allele, which originated in Amerindian populations by a crossing-over event between two widespread HLA-G alleles, was identified in 18 individuals. Neutrality tests evidenced that natural selection has a complex part in the HLA-G coding region. Although balancing selection is the type of selection that shapes variability at a local level (Native American populations), we have also shown that purifying selection may occur on a worldwide scale. Moreover, the balancing selection does not seem to act on the coding region as strongly as it acts on the flanking regulatory regions, and such coding signature may actually reflect a hitchhiking effect.Genes and Immunity advance online publication, 3 October 2013; doi:10.1038/gene.2013.47.

Densidades e arranjos populacionais de milho e componentes agronômicos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Uso do clorofilômetro portátil na determinação da adubação nitrogenada de cobertura em cultivares de feijoeiro

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Métodos híbridos de pontos interiores e de programação inteira 0-1 para problemas de custo de colheita da cana-de-açúcar e de custo de coleta e geração de energia relacionados à sua biomassa

Pós-graduação em Engenharia Elétrica - FEB

Anatomia e aspectos ultra-estruturais de pulvinos de leguminosas de cerrado

Pós-graduação em Ciências Biológicas (Botânica) - IBB

Enriquecimento de dados: uma pré-etapa em relação à limpeza de dados

Pós-graduação em Ciência da Computação - IBILCE

Estudo da habilidade de permanência de fêmeas da raça Canchim aos 76 meses de idade

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Divergência genética entre árvores matrizes de Guazuma ulmifolia Lam

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Algoritmo genético aplicado ao sequenciamento de picking e faturamento

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)