Documentação de convênios
URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/173
Trabalhos ténico-científico oriundos de convênios com universidades para oferta de turmas de mestrado e doutorados no Estado do Amazonas
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Resultados da Pesquisa
Item OTIMIZAÇÃO MULTIOBJETIVO DA COMPENSAÇÃO DE POTÊNCIA REATIVA EM REDES DE DISTRIBUIÇÃO CONSIDERANDO RESTRIÇÕES DE DISTORÇÃO HARMÔNICA(Universidade Federal do Pará, 2014) AZEVEDO, Manoel Socorro Santos; BEZERRA, Ubiratan HolandaThe correct location of capacitor banks in electric power distribution networks aims to compensate for excess reactive power flow through transmission lines, reducing operational costs by decreasing energy losses and increasing active power transmission capacity while ensuring appropriate voltage and power factor levels. The proliferation of nonlinear loads has introduced new challenges due to the harmful effects of harmonics on power quality. This thesis develops a computational tool using computational intelligence techniques with genetic algorithms (GA) for multiobjective optimization of reactive power compensation in electric distribution networks, capable of optimally locating and sizing compensation units while achieving economic benefits and complying with Brazilian power quality standards. The approach considers the use of capacitor banks and harmonic filters and applies the NSGA-II algorithm to determine Pareto-optimal solutions. The methodology enables the determination of reactive power compensation considering harmonic presence while maintaining compliance with normative limits on harmonic distortion.Item PROJETO MULTICRITÉRIO DE FILTROS HARMÔNICOS PASSIVOS PARA INSTALAÇÕES INDUSTRIAIS UTILIZANDO TÉCNICAS DE INTELIGÊNCIA COMPUTACIONAL(Universidade Federal do Pará, 2013) LEITE, Jandecy Cabral; TOSTES, Maria Emília de LimaDue to the industrial growth in Northern Brazil, especially at the Manaus Industrial Pole (PIM), mathematical tools are needed to assist experts in selecting and sizing harmonic filters that neutralize the harmful effects of harmonics generated by nonlinear loads and ensure compliance with power quality standards. Additionally, passive harmonic filters (PHF) can act as reactive power compensators, achieving significant energy billing savings. This thesis develops a mathematical method and a computational tool for selecting the configuration and design parameters of PHFs in industrial systems, formulating the problem as a multi-objective optimization that considers both harmonic distortion reduction and the project's economic effectiveness, complying with Brazilian and international standards. The computational solution is based on the NSGA-II genetic algorithm, generating a Pareto front of optimal solutions that allow designers to select the most suitable option. The tool includes innovative features, such as automatic selection of filter configuration and number of branches, and considers various operational scenarios. Validation was performed through practical examples that demonstrated the advantages of the proposed method.Item UMA NOVA SOLUÇÃO PARA A OTIMIZAÇÃO DO DESPACHO ECONÔMICO E AMBIENTAL UTILIZANDO METAHEURÍSTICAS DA COMPUTAÇÃO BIO-INSPIRADA(Universidade Federal do Pará, 2016) NASCIMENTO, Manoel Henrique Reis; NUNES, Marcus Vinícius AlvesDue to the significant industrial growth in Northern Brazil, especially at the Industrial Pole of Manaus (PIM), there has been an increased need for energy generation, which in this region is provided by thermoelectric plants (UTEs) in over 90% of its total. Thus, it became necessary to use computational tools that help specialists and operators make decisions about the optimal power dispatch, contemplating not only cost reduction but also reducing atmospheric pollution levels. This thesis presents a new solution proposal for the classic optimization problem of Economic Dispatch (ED) and Economic and Environmental Dispatch (EAD), using several Deterministic methods (Iteration Lambda, Quadratic Programming, Newton method) and Bio-Inspired Heuristic methods (Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Simulated Annealing, Grey Wolf Optimizer, and Artificial Bee Colony), as well as the Non-dominated Sorting Genetic Algorithm (NSGA-II and NSGA-III) for the EAD. The proposal includes shutting down generators with higher operating costs to reduce fuel costs and pollutant emissions like NOx and CO₂. The robustness of the methodology was validated with a set of ten generating units and three benchmark systems described in the literature, showing significant advantages of the new proposed solution.Item MODELO MATEMÁTICO PARA OTIMIZAÇÃO MULTIOBJETIVO DO DESPACHO ECONÔMICO AMBIENTAL DE USINAS TÉRMICAS USANDO O NSGA-II(Universidade Federal do Pará, 2017) MORAES, Nadime Mustafa; BEZERRA, Ubiratan HolandaOne of the priority tasks for thermoelectric plants is to supply the requested energy demand, ensuring the lowest possible cost. This task is especially important in the Northern Region of Brazil, particularly in the Manaus Industrial Hub (PIM), where much of the energy is supplied by Thermoelectric Power Plants (UTE). The selection of generators and their work regime is known as Economic Dispatch (DE). However, global concern about pollution caused by fossil fuels has made it essential to incorporate not only cost reduction but also the limitation of pollutant emissions in UTE operations. Thus, Environmental Economic Dispatch (DEA) emerges, aiming to simultaneously reduce costs and emissions. This thesis proposes an innovative mathematical model for DEA, using the NSGA-II evolutionary algorithm with two objective functions: fuel cost and amount of emissions. The model also introduces the Emissions Index, a new function to evaluate environmental contamination, considering the influence of the most harmful pollutants. The model was applied to engines of two UTEs in the city of Manaus, showing satisfactory results. The methodology proved robust when validated in two case studies: a set of ten thermal generating units and the IEEE 118-bus system.Item GESTÃO TERMOECOLÓGICA DE USINAS TERMOELÉTRICAS COM MOTORES DE COMBUSTÃO INTERNA: MODELO BASEADO EM ASPECTOS TÉCNICOS, ECONÔMICOS E AMBIENTAIS(Universidade Federal de Santa Catarina, 2017) SILVA, Wagner Ferreira; CAMPOS, Lucila Maria de SouzaAlthough there is a global trend toward renewable energy use, in thermoelectric plants, the main energy source remains fossil fuels. These plants, while generating the required electrical power for consumption, are significant sources of environmental pollution. This thesis develops a proposal for the thermoecological management of thermoelectric plants, jointly evaluating the thermal and environmental efficiency of internal combustion engines powered by fossil fuels, specifically fuel oil and natural gas. Different mathematical models were created and used in the development of procedures integrating technical (efficiencies), economic (fuel consumption and cost), and environmental (emission index, ecological function, and eco-efficiency) aspects. For the first time, the concept of entransy is applied to evaluate engine efficiency and to enhance the ecological function initially developed by Angulo-Brown. The concept of eco-efficiency was employed in the multi-objective optimization of load dispatch, allowing managers to evaluate different simulations in pursuit of higher thermoecological efficiency. Practical evaluation was carried out through the application of these procedures in a specific software for the type of thermoelectric plants analyzed. The main results include theoretical advances in thermoecological management and the creation of a practical tool for data analysis and decision-making. The effectiveness of the proposed procedures was demonstrated in real cases with different generation and fuel type scenarios.Item METODOLOGIA DE PLANEJAMENTO PARA INSERÇÃO DE GERADORES FOTOVOLTAICOS EM REDES ELÉTRICAS ISOLADAS E SUPRIDAS POR GERADORES A DIESEL(Universidade Federal do Pará, 2013) GONÇALVES, Cláudio; VIEIRA, João Paulo AbreuRenewable energy sources based on photovoltaic generation (PVG) are promising energy alternatives to complement conventional, centralized power generation, as the diesel thermal plants supplying power to isolated grids in cities and remote locations in the Amazon Region. The allocation and sizing of generators for distributed generation application (DG) is a challenging problem, with technical and economic implications related to the planning, design and operation of these systems. Particularly, the PVG presents added difficulty as it is a function of environmental conditions, mainly temperature and solar radiation. This thesis presents an analytical methodology to allocate and size active power photovoltaic generation units with embedded DC/AC inverter (PVGI) to be integrated as concentrated or dispersed generation in isolated medium voltage electrical grids. The proposed methodology considers multiple objectives to be reached namely: improving the electrical grid voltage profile; reducing active power losses; and reducing the diesel generation participation, providing, this way, a reduction in diesel oil consumption and in the environmental pollution. The global obtained solution of the proposed method is a weighted commitment to these goals, presenting different weights according to priorities established in the electrical system under planning. To validate the proposed methodology, the IEEE 33 and 69 buses networks and an isolated real electrical system were modeled and simulated. The real electrical system is located in Aveiro City, in the Amazon region, Brazil. The simulation results obtained demonstrated that the proposed methodology is effective in providing a solution with significant improvement in voltage profile, active power losses reduction, and diesel generation participation reduction, according to viable technical and economic indicators to the PVGI integration in the isolated electrical grid.Item SOLUÇÃO PARA O DESPACHO ECONÔMICO AMBIENTAL DE UM SISTEMA DE GERAÇÃO TÉRMICA POR RECOZIMENTO SIMULADO(Universidade Federal do Pará, 2018) BRITO JÚNIOR, Jorge de Almeida; NUNES, Marcus Vinícius AlvesIn recent years, population and government concerns about environmental protection have increased, while the use of fossil fuels for electricity generation remains high due to their availability and the consolidated technology of thermal plants. In this context, it has become common to adopt methodologies to optimize thermoelectric plant operations, considering both fuel costs and pollutant emissions. This PhD thesis aims to apply multiobjective optimization to the environmental economic dispatch (DEA) of thermal plants using simulated annealing, comparing the obtained results with other metaheuristic techniques. This tool was applied with a fitness function involving two objectives — cost and emissions — to find the optimal solution, taking into account the shutdown of less efficient engines, thus ensuring the reduction of financial costs and pollution.Item PRÉ-DESPACHO DE CARGA EM USINAS TERMOELÉTRICAS CONSIDERANDO A GESTÃO DA MANUTENÇÃO VIA LÓGICA FUZZY(Universidade Federal do Pará, 2018) FONSECA JUNIOR, Milton; BEZERRA, Ubiratan HolandaThis thesis presents a new proposal for load pre-dispatch considering the technical conditions of the engines of thermoelectric power plants by combining several maintenance and diagnostic techniques and using computational intelligence based on fuzzy logic. Diagnosis of the technical conditions of the engines is done using lubricant analysis, vibration analysis, and thermography. With this data and statistical analysis it is possible to predict when an engine can fail and consider this in the load pre-dispatch. To increase engine reliability and power supply, a Maintenance Management Program (MMP) was developed using management tools, applying only four TPM (Total Productive Maintenance) pillars and combining them with predictive maintenance and diagnostics, thus allowing the reduction of failures of plant equipment. Some results achieved after the implementation are: reduction of the annual maintenance cost, reduction of corrective maintenance, increase of the MTBF (Mean Time Between Failures), and decrease of MTTR (Mean Time To Repair) in all areas. In addition, the proposed pre-dispatch scheme ensures the demanded power with a high degree of reliability and quality.Item Avaliação da Distorção Harmônica Total de Tensão no Ponto de Acoplamento Comum Industrial Usando o Processo KDD Baseado em Medição(Universidade Federal do Pará, 2018) OLIVEIRA, Edson Farias de; TOSTES, Maria Emília de LimaIn recent decades, the transformation industry has introduced increasingly faster and more energy-efficient products for residential, commercial, and industrial use. However, these loads, due to their non-linearity, have significantly contributed to increased voltage harmonic distortion levels, according to Power Quality indicators. This thesis proposes a procedure based on the Knowledge Discovery in Databases (KDD) process to identify impactful loads on voltage harmonic distortions at the Point of Common Coupling (PCC). The methodology involves data collection and analysis with data mining techniques such as Decision Tree and Naïve Bayes applied to data collected by quality meters installed at the main loads and the PCC of an industrial consumer. The process includes data collection, cleaning, transformation, and evaluation steps. The results showed that the KDD process is applicable in analyzing Total Harmonic Distortion of Voltage, allowing the identification of the most impactful loads, with the most significant being the seventh current harmonic of the air conditioning units.Item Modelo híbrido baseado em séries temporais e redes neurais para previsão da geração de energia eólica(Universidade Federal do Pará, 2018) ALENCAR, David Barbosa de; AFFONSO, Carolina de Mattos; OLIVEIRA, Roberto Célio Limão deElectric power generation through wind turbines is one of the practically inexhaustible alternatives for clean energy. However, advances in science and technology are still needed to ensure greater uniformity in generation and increase the participation of wind energy in the energy matrix. This thesis proposes the development of prediction models for wind speed and energy generation over different time horizons — ultra-short, short, medium, and long-term — using computational intelligence techniques, such as SARIMA models and Artificial Neural Networks (ANN), as well as hybrid models combining these approaches. The methodology was applied using meteorological data from the Petrolina/PE station, from the SONDA database, between 2004 and 2017. The results demonstrated that the proposed hybrid model showed better performance, especially for the hourly forecast horizon, significantly contributing to the reliability and security of wind energy integration into the electrical system.