Aplicação de redes neurais em análise de viabilidade econômica de co-geração de energia elétrica

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Viabilidade econômica da venda de energia elétrica em co-geração sob condições de risco: um estudo de caso

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Rentabilidade e risco da produção de milho safrinha geneticamente modificado na região de Guaíra-SP

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Modelo enxuto de gerenciamento multiprojetos baseado na corrente crítica

Pós-graduação em Engenharia Mecânica - FEG

Modelo de solvatação teórica de flavonóis

Neste trabalho, nós usamos uma combinação da simulação Monte Carlo e o modelo quântico INDO/S-CI para investigar os efeitos de solvente nos espectros de absorção eletrônica dos flavonols quercetina e kaempferol solvatados em metanol. O estudo foi conduzido realizando cálculos ao nível de INDO/S-CI em várias configurações estatisticamente relevantes produzidas pela simulação Monte Carlo. Usando a função de autocorrelação da energia, nós reduzimos de forma segura o número necessário de cálculos quânticos a serem realizados para se obter o valor médio da energia de transição π --- π* da quercetina e kaempferol em metanol usando diferentes camadas de solvatação. Além disso, uma cuidadosa investigação das pontes de hidrogênio formadas no curso da simulação Monte Carlo foi realizada. Como poderá ser notado mais adiante, nossos resultados estão de muito bom acordo com os resultados experimentais disponíveis.

Simulação de perfis nucleares de poço em formações complexas

A identificação e descrição dos caracteres litológicos de uma formação são indispensáveis à avaliação de formações complexas. Com este objetivo, tem sido sistematicamente usada a combinação de ferramentas nucleares em poços não-revestidos. Os perfis resultantes podem ser considerados como a interação entre duas fases distintas: • Fase de transporte da radiação desde a fonte até um ou mais detectores, através da formação. • Fase de detecção, que consiste na coleção da radiação, sua transformação em pulsos de corrente e, finalmente, na distribuição espectral destes pulsos. Visto que a presença do detector não afeta fortemente o resultado do transporte da radiação, cada fase pode ser simulada independentemente uma da outra, o que permite introduzir um novo tipo de modelamento que desacopla as duas fases. Neste trabalho, a resposta final é simulada combinando soluções numéricas do transporte com uma biblioteca de funções resposta do detector, para diferentes energias incidentes e para cada arranjo específico de fontes e detectores. O transporte da radiação é calculado através do algoritmo de elementos finitos (FEM), na forma de fluxo escalar 2½-D, proveniente da solução numérica da aproximação de difusão para multigrupos da equação de transporte de Boltzmann, no espaço de fase, dita aproximação P₁, onde a variável direção é expandida em termos dos polinômios ortogonais de Legendre. Isto determina a redução da dimensionalidade do problema, tornando-o mais compatível com o algoritmo FEM, onde o fluxo dependa exclusivamente da variável espacial e das propriedades físicas da formação. A função resposta do detector NaI(Tl) é obtida independentemente pelo método Monte Carlo (MC) em que a reconstrução da vida de uma partícula dentro do cristal cintilador é feita simulando, interação por interação, a posição, direção e energia das diferentes partículas, com a ajuda de números aleatórios aos quais estão associados leis de probabilidades adequadas. Os possíveis tipos de interação (Rayleigh, Efeito fotoelétrico, Compton e Produção de pares) são determinados similarmente. Completa-se a simulação quando as funções resposta do detector são convolvidas com o fluxo escalar, produzindo como resposta final, o espectro de altura de pulso do sistema modelado. Neste espectro serão selecionados conjuntos de canais denominados janelas de detecção. As taxas de contagens em cada janela apresentam dependências diferenciadas sobre a densidade eletrônica e a fitologia. Isto permite utilizar a combinação dessas janelas na determinação da densidade e do fator de absorção fotoelétrico das formações. De acordo com a metodologia desenvolvida, os perfis, tanto em modelos de camadas espessas quanto finas, puderam ser simulados. O desempenho do método foi testado em formações complexas, principalmente naquelas em que a presença de minerais de argila, feldspato e mica, produziram efeitos consideráveis capazes de perturbar a resposta final das ferramentas. Os resultados mostraram que as formações com densidade entre 1.8 e 4.0 g/cm³ e fatores de absorção fotoelétrico no intervalo de 1.5 a 5 barns/e^-, tiveram seus caracteres físicos e litológicos perfeitamente identificados. As concentrações de Potássio, Urânio e Tório, puderam ser obtidas com a introdução de um novo sistema de calibração, capaz de corrigir os efeitos devidos à influência de altas variâncias e de correlações negativas, observadas principalmente no cálculo das concentrações em massa de Urânio e Potássio. Na simulação da resposta da sonda CNL, utilizando o algoritmo de regressão polinomial de Tittle, foi verificado que, devido à resolução vertical limitada por ela apresentada, as camadas com espessuras inferiores ao espaçamento fonte - detector mais distante tiveram os valores de porosidade aparente medidos erroneamente. Isto deve-se ao fato do algoritmo de Tittle aplicar-se exclusivamente a camadas espessas. Em virtude desse erro, foi desenvolvido um método que leva em conta um fator de contribuição determinado pela área relativa de cada camada dentro da zona de máxima informação. Assim, a porosidade de cada ponto em subsuperfície pôde ser determinada convolvendo estes fatores com os índices de porosidade locais, porém supondo cada camada suficientemente espessa a fim de adequar-se ao algoritmo de Tittle. Por fim, as limitações adicionais impostas pela presença de minerais perturbadores, foram resolvidas supondo a formação como que composta por um mineral base totalmente saturada com água, sendo os componentes restantes considerados perturbações sobre este caso base. Estes resultados permitem calcular perfis sintéticos de poço, que poderão ser utilizados em esquemas de inversão com o objetivo de obter uma avaliação quantitativa mais detalhada de formações complexas.

Estudo da contribuição do espalhamento nuclear não elástico na trajetória mais provável de prótons em alvo homogêneo composto de água

The Therapy with proton beam has shown more e ective than Radiotherapy for oncology treatment. However, to its planning use photon beam Computing Tomography that not considers the fundamentals di erences the interaction with the matter between X-rays and Protons. Nowadays, there is a great e ort to develop Tomography with proton beam. In this way it is necessary to know the most likely trajectory of proton beam to image reconstruction. In this work was realized calculus of the most likely trajectory of proton beam in homogeneous target compound with water that was considered the inelastic nuclear interaction. Other calculus was the analytical calculation of lateral de ection of proton beam. In the calculation were utilized programs that use Monte Carlo Method: SRIM 2006 (Stopping and Range of Ions in Matter ), MCNPX (Monte Carlo N-Particle eXtended) v2.50. And to analytical calculation was employed the software Wolfram Mathematica v7.0. We obtained how di erent nuclear reaction models modify the trajectory of proton beam and the comparative between analytical and Monte Carlo method

Modelagem matemática aplicada a precificação de opções

The mathematical models are critical to determine theoretical prices of options and analyze whether they are overrated or underrated. This information strongly influence in operations carried out by the investor. Therefore, it is necessary that the employee model present high degree of reliability and be consistent with the reality of investment to which it is intended. In this sense, this dissertation aims to apply the steps of mathematical modeling in the Pricing of options for decision making in the investment of a hydroelectric power plant. Was used a Monte Carlo simulation, with the Latin Hypercube Method, to determine the volatility of returns of the project. In order to validate the proposed model, compared to the results found by the Binomial Model, which is one of the models most used in this type of investment. The results reinforce the hypothesis that the mathematical modeling with the Binomial Model is critical to investment decision-making in hydroelectric power

Viabilidade econômica da venda de energia elétrica em cogeração sob condições de risco: um estudo de caso

The availability of the electrical energy, in sufficient quantities and in competitive prices is a crucial factor to the economic development. The trade-in of the excess electrical energy produced in a system of cogeneration can be seen as an alternative to the creation of an additional source of revenues for ethanol power plants sector, besides contributing to the complementation of the Brazilian electrical headquarter with renewable sources. The objective of this study was to evaluate the economic feasibility of the implementation of a cogeneration electrical central using the excess of sugar cane bagasse and selling the excess of electrical energy with prices of the market. An ethanol power plant located in the state of Sao Paulo was used to this study. It was used the case study methodology, evaluating the potential of the investment under the viewpoint of the Net Present Value (NPV), Payback and Internal Rate of Return (IRR), and complementing the results of the Accounting Results (AC). It was created three alternative scenarios to reflect the level of the risk of every studied situation: the most likely, an optimistic and a pessimistic, each one with its assumptions. The Monte Carlo Simulations was used to insert the elements of risk to each scenario. The results showed that the project is feasible in all NPV scenarios. And the Payback and IRR analysis confirmed these evidences. The valuation with the AR showed that the project is most risky at the pessimistic scenario, but is feasibly in the most likely and the optimistic scenarios. It was concluded that the project is economic viable. However, the economic viability shown in the results is based on the maintenance of the future prices on the levels of the historical prices used in the analysis.

Rentabilidade e Risco da Produção de Milho Safrinha Geneticamente Modificado e Convencional na Região de Guaíra/sp

The objective of this study was to dimension the economic risks and returns on adopters of genetically modified (GM) maize in one of the major corn producing regions of São Paulo state. We performed analysis of variation of the quantities and prices of insecticides used, productivity gains, and variation in the price differentials between GM maize and conventional hybrids seeds, according to account to the maize prices oscillation during the period studied. The net benefits methodology was used, in other words, the economic gains minus the costs of GM technology under risk conditions were calculated. The net benefits was calculated as a function of four critical variables: 1) GM maize productivity; 2) costs of pest control; 3) maize price; 4) GM seeds cost. The probability distribution functions of these critical variables were estimated and included in the net benefit equation. Using the Monte Carlo simulation methodology, the following indicator sets were estimated: central tendency measurements, variability in net benefits (total benefits minus total costs), sensitivity analysis of the net benefits in relation to the critical variables, and finally, a map of the risk to GM technology adopters. These indicators allow one to design economic scenarios associated with their probability of occurring. The results showed probability of 85% to positive gains to the farmers who adopted the transgenic maize seed cultivation. The variable with the greatest impact on the farmers' income was the reduction in productivity loss, that means, as higher is the maize productivity, higher will be the net income. The average gain was US$ 137,41 (R$ 2.45/US$)per hectare with the adoption of transgenic maize seed when compared to conventional maize seed.

Eficiência energética de sistemas de produção de mamona no Estado de Minas Gerais

The objective of this study is to determine the economical and energetic efficiency of the castor bean culture in "Zona da Mata" and South of Minas Gerais. Through the method of simulation "Monte Carlo", we verified the probabilities of occurrence of the economical, cultural and energetic efficiency indexes. In relation to the production systems of castor bean in Minas Gerais in the season 2005/2006, we established that the variables price and productivity were the most noticeable for the producers from "Zona da Mata", while in the South of Minas it was productivity. We verified that the probability of the economical efficiency index to be lower than one was 43,26% for the producers from "Zona da Mata" and 39,57% for the ones from the South of Minas. The medium price received covered the medium costs of production. However, we observed that the medium costs in these regions of Minas Gerais, were over the minimum price. Regarding the energetic analysis, the results showed that the systems in the regions studied in Minas Gerasi, presented average of cultural efficiency indexes of 8,26 and 18,89. We concluded that despite the result being favorable from the energetic point of view, from the economical sustainability point of view there is the need of a more effective support policy for the castor bean, taking into consideration that the expectations of the producers with PNPB were not confirmed.

Modelos lineares generalizados bayesianos para dados longitudinais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Aplicação do valor presente ajustado (APV) para avaliação do fluxo de caixa de uma empresa do setor automotivo no sistema inovar auto

The automobile industry shows relevance inside the Brazilian industrial scenario since it contributes with the development of a significant chain of supply, distributors, workshops, publicity agencies and insurance companies in the internal market, aside from being one of the five biggest worldwide market. Thereby, the federal government decreed in Dec, 17th 2012 by Law nº 12.715 the Inovar-Auto Program. As the Adjusted Present Value (APV) is highly recommended, although not yet widespread to public politics of tax reduction, this work intends to apply the APV method on the cash flow analysis of an automobile sector's company, which has recently installed in national territory and wants to rely with governmental incentives proposed by Inovar-Auto Program. The developed work evaluates the company's current cash flow stochastically from mathematical modeling of variables such as price, demand and interest rate through probability distributions with the assist of Crystal Ball software, a Microsoft Excel Add-in, generating different scenarios from Monte Carlo Simulation. As results probabilities situations have been evaluated until the end of the Inovar-Auto's conducted period, in 2017. Beside APV others indicator such as Internal Rate of Return (IRR) and payback period were estimated for the investment project. For APV a sampling distribution with only 0.057% of risk, IRR of 29% were obtained and estimated project payback period was 4.13 years

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model