Comparação de métodos baseados em algoritmos genéticos para ajuste coordenado de estabilizadores de sistemas de potência

Essa dissertação de mestrado apresenta um estudo comparativo entre três metodologias baseadas em algoritmos genéticos para ajuste coordenado de estabilizadores de sistemas de potência (ESP). Os procedimentos de ajuste do ESP são formulados como um problema de otimização, a fim de: 1) maximizar o coeficiente de amortecimento mínimo do sistema em malha fechada; 2) maximizar o somatório de todos os coeficientes de amortecimento do sistema em malha fechada; e 3) deslocar os modos eletromecânicos poucos amortecidos ou mal amortecidos para uma zona pré-escrita no plano s. As três metodologias consideram um conjunto de condições de operacionais pré-especificadas. O sistema elétrico foi representado por equações no espaço de estado e as matrizes associadas com a modelagem foram obtidas por meio da versão acadêmica do programa PacDyn. As simulações foram realizadas usando o MATLAB. As metodologias foram aplicadas no conhecido sistema teste New England.

Metodologia para utilização de algoritmos genéticos em modelos de simulação computacional em ambientes de manufatura

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Algoritmo genético aplicado ao controle do mosquito transmissor da dengue

Pós-graduação em Biometria - IBB

Planejamento de sistemas de distribuição de energia elétrica de média tensão através de um algoritmo de busca dispersa

Pós-graduação em Engenharia Elétrica - FEIS

Índices de confiabilidade devido a vegetação e planejamento de podas de árvores em redes de distribuição

Pós-graduação em Engenharia Elétrica - FEIS

Espaços vetoriais e topológicos de intervalos generalizados com alguns conceitos de cálculo e otimização intervalar

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Otimização de problemas multimodais usando meta-heurísticas evolutivas

Pós-graduação em Engenharia Elétrica - FEIS

Software baseado em rede neural artificial desenvolvido por meio de algoritmo genético para a classificação morfológica de blastocistos bovinos

Pós-graduação em Biociências - FCLAS

Desenvolvimento de uma ferramenta de otimização para avaliar a expansão da transmissão de energia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A new probabilistic canopy dynamics model (SLCD) that is suitable for evergreen and deciduous forest ecosystems

There are strong uncertainties regarding LAI dynamics in forest ecosystems in response to climate change. While empirical growth & yield models (G&YMs) provide good estimations of tree growth at the stand level on a yearly to decennial scale, process-based models (PBMs) use LAI dynamics as a key variable for enabling the accurate prediction of tree growth over short time scales. Bridging the gap between PBMs and G&YMs could improve the prediction of forest growth and, therefore, carbon, water and nutrient fluxes by combining modeling approaches at the stand level.Our study aimed to estimate monthly changes of leaf area in response to climate variations from sparse measurements of foliage area and biomass. A leaf population probabilistic model (SLCD) was designed to simulate foliage renewal. The leaf population was distributed in monthly cohorts, and the total population size was limited depending on forest age and productivity. Foliage dynamics were driven by a foliation function and the probabilities ruling leaf aging or fall. Their formulation depends on the forest environment.The model was applied to three tree species growing under contrasting climates and soil types. In tropical Brazilian evergreen broadleaf eucalypt plantations, the phenology was described using 8 parameters. A multi-objective evolutionary algorithm method (MOEA) was used to fit the model parameters on litterfall and LAI data over an entire stand rotation. Field measurements from a second eucalypt stand were used to validate the model. Seasonal LAI changes were accurately rendered for both sites (R-2 = 0.898 adjustment, R-2 = 0.698 validation). Litterfall production was correctly simulated (R-2 = 0.562, R-2 = 0.4018 validation) and may be improved by using additional validation data in future work. In two French temperate deciduous forests (beech and oak), we adapted phenological sub-modules of the CASTANEA model to simulate canopy dynamics, and SLCD was validated using LAI measurements. The phenological patterns were simulated with good accuracy in the two cases studied. However, IA/max was not accurately simulated in the beech forest, and further improvement is required.Our probabilistic approach is expected to contribute to improving predictions of LAI dynamics. The model formalism is general and suitable to broadleaf forests for a large range of ecological conditions. (C) 2014 Elsevier B.V. All rights reserved.

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

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

Desenvolvimento de solução para o problema de alocação de navios em berços de terminais portuários: aplicação de algoritmos genéticos e otimização por nuvens de partículas

This work proposes two optimization algorithms for the solution of the Berth Allocation Problem (PAB). Due to the economic development of the country, it became necessary for the improvement of means of transport, which mainly shipping. For this, you need a better system management port, you will receive a lot of ships carrying cargo. In this work the PAB is approached so that the goals are to reduce costs and time handling in ports. For this, we applied two computational techniques, genetic algorithms and optimization for cloud particles, to obtain the best results for this problem. The results obtained with each type of algorithm are compared to conclude which method is more efficient for the port system

Uso de algoritmos genéticos na otimização do sistema de coleta do palhiço de cana-de-açúcar

The Brazilian government has convinced the world that ethanol deriving from sugar cane is a promissory means of sustainable fuel for vehicles. There is a great growth of ex vehicles , i.e, run both by ethanol and gasoline, due to competent automotive industries and e cient alcohol production technology. In 2009 and 2010 the ethanol production was 25.7 billion liters and 53.8% of sugar cane production was destined to alcohol production. Nevertheless, the sugar production also derived from sugar cane should increase in 2011. Brazil produced 33 million tons of sugar in the last harvest. With sugar cane on the rise production is arising new environmental problems. The harvest using mechanized cut besides improving the logistic transportation system leaves the generating residue in the eld. This residue is a mixture of straw, leavings and scrap of sugar cane named sugar cane crop residue and corresponds to 30% of biomass and can be burned and produce electricity by cogeneration. But the transport the sugar cane crop from the eld is expensive due costs involved in the transport system. This work aims to propose a formulation for the bales collecting problem from sugar cane eld to mill that minimize the costs involved in the transport system. The computational tests use the C++ language and an algorithm based on genetic algorithms techniques

Modelos matemáticos e computacionais em dengue

This work was developed starting the study of traditionals mathematical models that describe the epidemiology of infectious díseases by direct or indirect transmission. We did the classical approach of equilibrium solutions search, its analysis of stability analytically and by numerical solutions. After, we applied these techniques in a compartimental model of Dengue transmission that consider the mosquito population (susceptible vector Vs and 'infected vector VI), human population (suseeptíble humans S, infected humans I and recovered humans R) and just one sorotype floating in this population. We found the equilibrium solutions and from their analises, it was possible find the reprodution rate of dísease and which define if the disease will be endemic or not in the population.- ext, we used the method described a..~, [1] to study the infíuence of seasonalíty at vírus transmission, when it just acts on one of rates related with the vector. Lastly, we made de modeling considering the periodicity of alI rates, thereby building, a modeI with temporal dependence that permits to study periodicity of transmission through of the approach of parametrical ressonance and genetic algorithm

Novo algoritimo genético para problemas de cobertura de conjuntos

The Set Covering Problem (SCP) plays an important role in Operational Research since it can be found as part of several real-world problems. In this work we report the use of a genetic algorithm to solve SCP. The algorithm starts with a population chosen by a randomized greedy algorithm. A new crossover operator and a new adaptive mutation operator were incorporated into the algorithm to intensify the search. Our algorithm was tested for a class of non-unicost SCP obtained from OR-Library without applying reduction techniques. The algorithms found good solutions in terms of quality and computational time. The results reveal that the proposed algorithm is able to find a high quality solution and is faster than recently published approaches algorithm is able to find a high quality solution and is faster than recently published approaches using the OR-Library.