Este estudo mostra o desenvolvimento de um controlador da classe MPC Model Predictive Control, ou controle preditivo com modelo, para ser utilizado no reator de amônia da Unidade de Fertilizantes Nitrogenados da Bahia FAFEN-BA, da PETROBRAS, localizada em Camaçari/BA. A estratégia de controle visa manter as temperaturas de saída de cada um dos leitos catalíticos do reator dentro de limites adequados através da manipulação das válvulas de controle instaladas na corrente de alimentação do equipamento. O controlador escolhido foi de horizonte de predição infinito com faixas nas variáveis controladas. Adicionalmente, o controlador contém, em uma única camada, um componente de otimização econômica com o objetivo de maximizar o teor de amônia na saída do reator. A função econômica que dá a direção de otimização consiste em um modelo rigoroso de estado estacionário do reator capaz de calcular a fração molar de amônia na saída do equipamento quando são conhecidas as condições da corrente de alimentação e o valor das variáveis manipuladas do controlador. Os resultados das simulações mostraram que o controlador proposto tem bom desempenho, tanto sob o aspecto de controle, no sentido de controlar o sistema quando este sofre perturbações, quanto sob a ótica de otimização econômica, maximizando a conversão de reagentes em amônia sempre que existem graus de liberdade disponíveis no sistema. Foi verificado que a consideração de um MPC de horizonte de predição infinito elimina a necessidade de considerar o gradiente reduzido da função econômica na função objetivo do controlador. Uma sintonia adequada do controlador permite que se considere o gradiente completo da função econômica sem que haja desvio permanente, ou offset, nas variáveis controladas mesmo quando o ponto ótimo de operação se encontra além da faixa de controle. / This study shows the development of a Model Predictive Control (MPC) to the ammonia reactor of PETROBRAS nitrogen fertilizers unit FAFEN-BA that is located in Camaçari/BA, Brazil. The main goal of the control strategy is to keep the temperature at the outlet of the catalyst beds inside adequate ranges by manipulating the feed flow rates to the reactor beds. It has been chosen an infinite horizon controller with control zones and an economic objective. The control and economic optimization are performed in a single layer structure where the objective is to maximize the ammonia content in the reactor outlet stream. The economic function which provides the optimization direction is based on a steady state rigorous model of the reactor that evaluates the ammonia molar fraction at the outlet stream assuming that the feed stream conditions and the manipulated variables are known. The proposed controller shows satisfactory performance in simulations either controlling the system when it faces external disturbances or optimizing the economic goal by increasing the ammonia conversion when degrees of freedom are available. It is shown that the adoption of the infinite horizon MPC eliminates the need to consider the reduced gradient of the economic function in the cost function of the controller. The proper tuning of the controller allows the consideration of the full gradient of economic function without producing offset in the controlled outputs even when the optimum operating point lays outside the control zones.

Com o objetivo de elaborar modelos matemáticos, visando à otimização da relação custo benefício e definir estratégias nutricionais considerando características de desempenho, de carcaça e variáveis de mercado, foi realizado experimento com frangos de corte fêmeas. Foram avaliados seis programas nutricionais para cada fase de crescimento (pré-inicial, inicial, crescimento I, crescimento II e final).Os tratamentos compreenderam rações baseadas em seis níveis de energia metabolizável aparente corrigida para balanço de nitrogênio (EMAn), mantendo-se a relação EMAn:nutrientes. Utilizando como tratamento controle (T4), os níveis nutricionais indicados por Rostagno et al. (2005),os demais corresponderam a -15%(T1), -10%(T2), -5%(T3), +5%(T5) e +10%(T6) em relação ao programa padrão. Para cada tratamento, foram utilizadas seis repetições com trinta aves , em um delineamento inteiramente casualizado. Foram avaliadas as características de desempenho e de carcaça aos 35, 42 e 49 dias de idade, e, após a obtenção das equações de regressão, realizada a análise econômica, através de simulações de cenários de mercado, para estabelecer os níveis nutricionais mais adequados em cada situação. Conclui-se que a melhora no desempenho decorrente do aumento da densidade nutricional de dietas de frangos de corte fêmea não deve ser interpretada como aumento da lucratividade. Sendo assim, os modelos matemáticos são úteis para estabelecer a relação entre variáveis de importância e essenciais para avaliação e determinação de planos nutricionais e forma de comercialização da aves adequados para a maximização do lucro. Os modelos matemáticos desenvolvidos possibilitam a predição de ganho de peso, consumo de ração e conversão alimentar e a otimização da lucratividade através da adequação dos níveis nutricionais e idade de abate, de acordo com as situações de mercado. / To elaborate mathematical models, aiming the optimization of cost-benefit ratio and define nutritional strategies considering performance, carcass caracteristics and market variables, was carried out an experiment with female broilers chickens. It was evaluated six nutritional programs for each phase of growth (pre-starter, starter, growth I, growth II and withdrawal). The treatments were based on six levels of metabolizable energy corrected to nitrogenm balance (AMEn), keeping the AMEn:nutrients ratio. Using as a control treatment (T4), nutritional levels acording to Rostagno et al. (2005), the others were calculated - -15%(T1), -10%(T2), -5%(T3), +5%(T5) and +10%(T6) compared to the standard program. For each treatment, was used six replicates with thirty birds, in a completely randomized design. Carcass and performance characteristics were evaluated at 35, 42 and 49 days of age and, after obtained the regression equations, it was elaborated an economic analysis to establish the best nutritional levels in each market situation. It was concluded that the improvement in performance due to increased nutrient density of diets of broilers female should not be interpreted as increased profitability. Thus, mathematical models are useful to establish the relationship between variables of importance and essential for evaluating and determining nutritional programs and manner of commercialization of birds suitable for profit maximization. The developed mathematical models are an important tool, because they allow prediction of variables such as weight gain, feed intake and feed conversion and the optimization through nutritional levels and slaughter age, according to market situations.

Com o objetivo de elaborar modelos matemáticos, visando à otimização da relação custo benefício e definir estratégias nutricionais considerando características de desempenho, de carcaça e variáveis de mercado, foi realizado experimento com frangos de corte fêmeas. Foram avaliados seis programas nutricionais para cada fase de crescimento (pré-inicial, inicial, crescimento I, crescimento II e final).Os tratamentos compreenderam rações baseadas em seis níveis de energia metabolizável aparente corrigida para balanço de nitrogênio (EMAn), mantendo-se a relação EMAn:nutrientes. Utilizando como tratamento controle (T4), os níveis nutricionais indicados por Rostagno et al. (2005),os demais corresponderam a -15%(T1), -10%(T2), -5%(T3), +5%(T5) e +10%(T6) em relação ao programa padrão. Para cada tratamento, foram utilizadas seis repetições com trinta aves , em um delineamento inteiramente casualizado. Foram avaliadas as características de desempenho e de carcaça aos 35, 42 e 49 dias de idade, e, após a obtenção das equações de regressão, realizada a análise econômica, através de simulações de cenários de mercado, para estabelecer os níveis nutricionais mais adequados em cada situação. Conclui-se que a melhora no desempenho decorrente do aumento da densidade nutricional de dietas de frangos de corte fêmea não deve ser interpretada como aumento da lucratividade. Sendo assim, os modelos matemáticos são úteis para estabelecer a relação entre variáveis de importância e essenciais para avaliação e determinação de planos nutricionais e forma de comercialização da aves adequados para a maximização do lucro. Os modelos matemáticos desenvolvidos possibilitam a predição de ganho de peso, consumo de ração e conversão alimentar e a otimização da lucratividade através da adequação dos níveis nutricionais e idade de abate, de acordo com as situações de mercado. / To elaborate mathematical models, aiming the optimization of cost-benefit ratio and define nutritional strategies considering performance, carcass caracteristics and market variables, was carried out an experiment with female broilers chickens. It was evaluated six nutritional programs for each phase of growth (pre-starter, starter, growth I, growth II and withdrawal). The treatments were based on six levels of metabolizable energy corrected to nitrogenm balance (AMEn), keeping the AMEn:nutrients ratio. Using as a control treatment (T4), nutritional levels acording to Rostagno et al. (2005), the others were calculated - -15%(T1), -10%(T2), -5%(T3), +5%(T5) and +10%(T6) compared to the standard program. For each treatment, was used six replicates with thirty birds, in a completely randomized design. Carcass and performance characteristics were evaluated at 35, 42 and 49 days of age and, after obtained the regression equations, it was elaborated an economic analysis to establish the best nutritional levels in each market situation. It was concluded that the improvement in performance due to increased nutrient density of diets of broilers female should not be interpreted as increased profitability. Thus, mathematical models are useful to establish the relationship between variables of importance and essential for evaluating and determining nutritional programs and manner of commercialization of birds suitable for profit maximization. The developed mathematical models are an important tool, because they allow prediction of variables such as weight gain, feed intake and feed conversion and the optimization through nutritional levels and slaughter age, according to market situations.

Este trabalho tem como objetivo estudar as características de uma coluna depropanizadora e propor uma estrutura de controle para esta planta. Essa coluna está localizada na unidade de craqueamento catalítico da Refinaria Presidente Bernardes, em Cubatão. O objetivo de controle é a especificação de um valor máximo de butano e componentes mais pesados (C4+) na corrente de topo e um valor máximo de propano e componentes mais leves (C3-) na corrente de fundo. Uma simulação da planta foi construída por meio do simulador de processos AspenOne® e os modelos referentes a vários pontos de operação e duas composições de carga distintas foram obtidos através da simulação integrada entre o Aspen® e o Simulink®. O software Matlab(TM) foi utilizado para executar o algoritmo de controle. O controlador aqui proposto é um IHMPC (Infinite Horizon Model Predictive Control) adaptado para sistemas com tempo morto e com faixas nas variáveis controladas. As incertezas na modelagem foram representadas por um conjunto de modelos lineares. Adicionalmente o controlador contém, na mesma camada, um componente de otimização econômica linear com o objetivo de minimizar o gasto energético do sistema ou até mesmo maximizar a pureza do destilado. As simulações permitiram que as estratégias de controle pudessem ser testadas e seus resultados discutidos. A análise dos testes mostra que o IHMPC aqui proposto é capaz de controlar a planta nos possíveis pontos de operação com um bom desempenho. / The objective of this work is to study the characteristics of a depropanizer column and to propose a predictive control structure for this plant. This column is located at the fluid catalytic cracking unit of the Presidente Bernardes Refinery, in Cubatão. The control objective of these columns is the specification of a maximum value of butane and heavier components (C4+) in the top stream and the maximum value of propane and lighter components (C3-) in the bottom stream. The plant was represented through the process simulator AspenOne® and the models for several operating points and two different feed compositions were obtained through the integrated simulation of Aspen® and Simulink®. The software Matlab(TM) was used to run the control algorithm. The controller proposed here is based on the IHMPC (Infinite Horizon Model Predictive Control) that was extended to time delayed systems and zone control. The model uncertainties are approximated by a set of linear models. In addition, the controller contains, in the same layer, an economic objective, which aims to minimize the energy contents of the operation and to maximize the purity of the distillate. The simulation allowed that the control strategies could be tested and the results discussed. The analysis of the tests showed that the proposed IHMPC is able to control the plant with acceptable performance.

This dissertation investigated farm management concerns faced by grain producers due to the acquisition of various precision agriculture technologies. The technologies evaluated in the three manuscripts included 1) auto-steer navigation, 2) automatic section control, and 3) autonomous machinery. Each manuscript utilized a multifaceted economic model in a whole-farm decision-making framework to determine the impact of precision agriculture technology on machinery management, production management, and risk management. This approach allowed for a thorough investigation into various precision agriculture technologies which helped address the relative dearth of economic studies of precision agriculture and farm management. Moreover, the research conducted on the above technologies provided a wide array of economic insight and information for researchers and developers to aid in the advancement of precision agriculture technologies. Such information included the risk management potential of auto-steer navigation and automatic section control, and the impact the technologies had on optimal production strategies. This dissertation was also able to provided information to guide engineers in the development of autonomous machinery by identifying critical characteristics and isolating the most influential operating machine. The inferences from this dissertation intend to be employed in an extension setting with the purpose of educating grain producers on the impacts of implementing such technologies.

Este estudo mostra o desenvolvimento de um controlador da classe MPC Model Predictive Control, ou controle preditivo com modelo, para ser utilizado no reator de amônia da Unidade de Fertilizantes Nitrogenados da Bahia FAFEN-BA, da PETROBRAS, localizada em Camaçari/BA. A estratégia de controle visa manter as temperaturas de saída de cada um dos leitos catalíticos do reator dentro de limites adequados através da manipulação das válvulas de controle instaladas na corrente de alimentação do equipamento. O controlador escolhido foi de horizonte de predição infinito com faixas nas variáveis controladas. Adicionalmente, o controlador contém, em uma única camada, um componente de otimização econômica com o objetivo de maximizar o teor de amônia na saída do reator. A função econômica que dá a direção de otimização consiste em um modelo rigoroso de estado estacionário do reator capaz de calcular a fração molar de amônia na saída do equipamento quando são conhecidas as condições da corrente de alimentação e o valor das variáveis manipuladas do controlador. Os resultados das simulações mostraram que o controlador proposto tem bom desempenho, tanto sob o aspecto de controle, no sentido de controlar o sistema quando este sofre perturbações, quanto sob a ótica de otimização econômica, maximizando a conversão de reagentes em amônia sempre que existem graus de liberdade disponíveis no sistema. Foi verificado que a consideração de um MPC de horizonte de predição infinito elimina a necessidade de considerar o gradiente reduzido da função econômica na função objetivo do controlador. Uma sintonia adequada do controlador permite que se considere o gradiente completo da função econômica sem que haja desvio permanente, ou offset, nas variáveis controladas mesmo quando o ponto ótimo de operação se encontra além da faixa de controle. / This study shows the development of a Model Predictive Control (MPC) to the ammonia reactor of PETROBRAS nitrogen fertilizers unit FAFEN-BA that is located in Camaçari/BA, Brazil. The main goal of the control strategy is to keep the temperature at the outlet of the catalyst beds inside adequate ranges by manipulating the feed flow rates to the reactor beds. It has been chosen an infinite horizon controller with control zones and an economic objective. The control and economic optimization are performed in a single layer structure where the objective is to maximize the ammonia content in the reactor outlet stream. The economic function which provides the optimization direction is based on a steady state rigorous model of the reactor that evaluates the ammonia molar fraction at the outlet stream assuming that the feed stream conditions and the manipulated variables are known. The proposed controller shows satisfactory performance in simulations either controlling the system when it faces external disturbances or optimizing the economic goal by increasing the ammonia conversion when degrees of freedom are available. It is shown that the adoption of the infinite horizon MPC eliminates the need to consider the reduced gradient of the economic function in the cost function of the controller. The proper tuning of the controller allows the consideration of the full gradient of economic function without producing offset in the controlled outputs even when the optimum operating point lays outside the control zones.

Energy production in power plants comes with both high costs and turnover whereas variations in the production strategy—that is, which boilers, coolers, or generators that should be running—have big impact on the economic result. This is especially true for a combined heat and power (CHP) plant where the production of district heating and electricity is linked, thus allowing for a higher flexibility in the production strategy and potential of increasing the revenue. Previous research states that thermo-economic optimization can have a great impact on economic result of power plants, but every power plant is operating under a unique set of conditions depending on its location, operating market, load demand, construction, surrounding, and the like, and comparable studies on CHP plants in Sweden are very few. This study aims to fill this research gap by evaluating savings potential of a CHP plant in Lidköping, Sweden by utilizing thermo-economic optimization with the approach of combining actual historical data from the power plant with mass-flow equations and constraints to construct a mathematical MODEST model that is optimized by linear programming. The result demonstrates a clear theoretical potential to improve earnings and the conclusion that the studied CHP would benefit by implementing optimization procedures or software to schedule production. The result was also comparable to previous research but varied over time, which highlights how unique conditions may impact the result.

<div>This dissertation develops an exclusive workflow driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System (IES). The objective of this research is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, coal, gas, wind, and solar). The main contribution of this dissertation addresses several major challenges in current optimization methods of the energy portfolios in IES. First, the feasibility of generating the synthetic time series of the periodic peak data. </div><div>Second, the computational burden of conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models.</div><div>Third, the inadequacies of previous studies about the comparisons of the impact of the economic parameters.</div><div><br></div><div>Several algorithmic developments are proposed to tackle these challenges. A stochastic-based optimizer, which employs Gaussian Process modeling, is developed. The optimizer requires a large number of samples for its training, with each sample consisting of a time series describing the electricity demand or other operational and economic profiles for multiple types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads limited set of historical data, such as demand and weather data from past years. To construct the Reduced Order Models (ROMs), several data analysis methods are used, such as the Auto Regressive Moving Average (ARMA), the Fourier series decomposition, the peak detection algorithm, etc. The purpose of using these algorithms is to detrend the data and extract features that can be used to produce synthetic time histories that maintain the statistical characteristics of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit (FOM), the specific cash flow stream for each energy producer and the total Net Present Value (NPV). The Screening Curve Method (SCM) is employed to get the initial estimate of the optimal capacity. Results obtained from a model-based optimization of the Gaussian Process are evaluated using an exhaustive Monte Carlo search. </div><div><br></div><div>The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The proposed workflow can provide a comprehensive, efficient, and scientifically dependable strategy to support the decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of IES.</div><div><br></div>

Yes / Daily increasing use of tidal power generation proves its outstanding features as a renewable source. Due to environmental concerns, tidal current energy which has no greenhouse emission attracted researchers’ attention in the last decade. Additionally, the significant potential of tidal technologies to economically benefit the utility in long-term periods is substantial. Tidal energy can be highly forecasted based on short-time given data and hence it will be a reliable renewable resource which can be fitted into power systems. In this paper, investigations of effects of a practical stream tidal turbine in Lake Saroma in the eastern area of Hokkaido, Japan, allocated in a real microgrid (MG), is considered in order to solve an environmental/economic bi-objective optimization problem. For this purpose, an intelligent evolutionary multi-objective modified bird mating optimizer (MMOBMO) algorithm is proposed. Additionally, a detailed economic model of storage devices is considered in the problem. Results show the efficiency of the suggested algorithm in satisfying economic/environmental objectives. The effectiveness of the proposed approach is validated by making comparison with original BMO and PSO on a practical MG. / Iran National Science Foundation; Royal Academy of Engineering Distinguished Visiting Fellowship under Grant DVF1617\6\45

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs. / text