Teses em Engenharia Elétrica (Doutorado) - PPGEE/ITEC

URI Permanente para esta coleçãohttps://repositorio.ufpa.br/handle/2011/2317

O Doutorado Acadêmico inicio-se em 1998 e pertence ao Programa de Pós-Graduação em Engenharia Elétrica (PPGEE) do Instituto de Tecnologia (ITEC) da Universidade Federal do Pará (UFPA).

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Agora exibindo 1 - 7 de 7

Acesso aberto (Open Access)
Antenas compactas de microondas de banda larga e banda ultra-larga (UWB)
(Universidade Federal do Pará, 2011-12-16) MÉLO, Dilermando Ramalho de; DMITRIEV, Victor Alexandrovich; http://lattes.cnpq.br/0684541646225359
In the last years, with the sprouting of new services and devices for the system of mobile communication that have large bandwidths of operation band frequency and occupying small volumes, the development of new antennas of broad bands and with reduced dimensions if became one of the main challenges of the research in the field of antennas. In the present work, two structures of large bandwidth antennas and dimensions reduced had been analyzed and optimized. In the first part, the wire built-in folded monopole antenna (W-BFMA) was investigated and optimized in different feeding impedances. For modeling of antenna structure W-BFMA the numerical method of moments (MoM) was used, and for its optimization the methods: parametric, hill climbing and genetic algorithm (GA) were used. Computational programs based in the Matlab language had been developed for modeling, optimizing, and generation of the main characteristic curves of the antenna. In the second part, two different configurations of planar monopole antennas using the technology ultrawideband (UWB) had been investigated and optimized with the aid of commercial program CST - Microwave Studio. Both UWB antennas had been fed by a line of microstrip in the impedance of 50Ω. The UWB antenna with the small return loss was constructed and measured experimentally. The main characteristic curves of the antenna as return losses, gain and radiation patterns had been analyzed. The simulated results had been compared with the measured results.
Acesso aberto (Open Access)
Desenvolvimento a eventos discretos de um controlador de balanceamento de fases para sistemas legados de baixa tensão e microgrids
(Universidade Federal do Pará, 2019-06-10) VILCHEZ, José Ruben Sicchar; SILVA, José Reinaldo; http://lattes.cnpq.br/9317869378701106; COSTA JÚNIOR, Carlos Tavares da; http://lattes.cnpq.br/6328549183075122
In the up-grading of the legacy low-voltage system as urban microgrids, phase - balance algorithm development becomes useful and important to ensures robust and reliable load balancing, establish an efficient automation workflow among consumers, the legacy lowvoltage grid and the supervision center of the distribution network of electrical power. It constituting an alternative. This may constitute an alternative phase-balancing control system based on consumer units dynamic switching rather than electrical current injection by microgrids. Formal automation design of these algorithms become an interesting milestone for performance evaluation and properties validation for their insertion in the new microgrid architecture. This may evaluate the system's reliable performance when verifying dynamic properties as well as, the univocal solutions that ensure load transfer and load stability robustness of low-voltage grid, without operation interruptions neither conflicting events. This work, proposes a new phase-load- balancing control system based on combined algorithms resulting from a Hierarchical Petri net system design. Through this model it was obtained an optimized and reliable automated workflow of load balance in the low-voltage grid phases, with an efficient choice of consumer units for the switching process, aiming to obtain a robust steady state of load against unbalances between phases, and neutral current minimized. From the model obtained called “Transformer- Phase Balancing Controller” (T-PBC) were developed four integrated algorithms: the Load Transfer Algorithm, that calculates the load imbalance level and power to be transferred in the transformer phases; the Consumption Diagnose Algorithm, that identifies the load levels margins in each consumer unit; the Consumption Forecast Algorithm, that forecast the monthly energy future states in consumers; and the Switch Selection Algorithm, that selects the consumers units to switch based on the future state of energy consumption, the load level margins and the average of the energy future states. Based on the performance results, it was obtained, the efficient reduction of the neutral current and the load average unbalance in the low-voltage grid phases, with load stability robustness about three months, making it an efficient alternative system against load unbalances in the legacy low-voltage grid and the microgrids.
Acesso aberto (Open Access)
Metodologia de planejamento para inserção de geradores fotovoltaicos em redes elétricas isoladas e supridas por geradores a diesel
(Universidade Federal do Pará, 2013-09-05) GONÇALVES, Cláudio; TOSTES, Maria Emília de Lima; http://lattes.cnpq.br/4197618044519148; VIEIRA, João Paulo Abreu; http://lattes.cnpq.br/8188999223769913
Renewable 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.
Acesso aberto (Open Access)
Modelo híbrido baseado em séries temporais e redes neurais para previsão da geração de energia eólica
(Universidade Federal do Pará, 2018-08-30) ALENCAR, David Barbosa de; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720
The electric power generation through wind turbines is one of the practically inexhaustible alternatives sources of electric power. It is considered a source of clean energy, but still requires a lot of research to develop science and technologies that ensure uniformity in generation, providing a greater participation of this source in the energy matrix in Brazil as in the world, because the wind presents abrupt variations speed, density, and other important variables. In wind-based electrical systems, each forecast horizon is applied to a specific segment, forecast of minutes, hours, weeks, months, and future years of wind behavior, in order to evaluate the availability of energy for the next period, relevant information in the dispatch of the generating units and in the control of the electric system. This thesis aimed to develop ultra-short, short, medium and long-term prediction models of wind speed, based on computational intelligence techniques, using Artificial Neural Networks, SARIMA models and hybrid models and to predict the generation capacity of power for each horizon. For the application of the methodology, the meteorological variables of the database of the national environmental data system SONDA, Petrolina station, were used for the period from January 1st, 2004 to March 31st, 2017. The performance of the models was compared with 5, 10 and 20 steps forward, considering minutes, hours, days, weeks, months and years as the forecast horizon. The hybrid model obtained better response in the forecasts, among which the hour horizon was highlighted.
Acesso aberto (Open Access)
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 Alves; http://lattes.cnpq.br/9533143193581447
Due to the significant industrial growth in the North of Brazil, especially at the Industrial Pole of Manaus (PIM), it has been an increased necessity for energy generation, which in this region is provided by thermoelectric plants (UTEs) in over 90% of its total. Thus, it became necessary the use of computational tools that help the specialists or operators of electrical systems, for making decisions about the optimal power dispatch of each generating unit that contemplate not only to reduce costs but also reduce the atmospheric pollution levels. Optimization of Economic Dispatch (ED) is one of the oldest and most important tasks in power plant management, and currently, due to growing concerns about the environment, this problem is extended to the optimization of the Economic and Environmental Dispatch (EAD). This thesis has as main objective to analyze a new proposal to solve the old optimization problem of ED and the EAD implemented by several Deterministic methods (Iteration Lambda, Quadratic Programming and Newton method) and Heuristic methods (Genetic Algorithms, Particle Swarm, Differential evolution, Simulated Annealing, Optimization by Grey Wolf and Artificial Bee Colonies) for the ED problem. Non-dominated Sorting Genetic Algorithms (NSGA II and NSGA III), were used for evaluating the problem of EAD, considering the shutdown of the generators with higher losses and thus reducing the fuel cost. The method of incremental cost and transmission losses are used to determine the best active power values for each generating unit. It was ensured the energy balance between the total generated power, the demand of the electrical system, losses and minimizing, on the other hand, the total cost of fuel, reducing emissions, and further improving efficiency not only for generators but also to UTE as a whole. Consequently, the proposed new solution has the following contributions: contemplates the turning off generation systems that have higher fuel cost, reducing the overall costs and enabling predictive maintenance on these machines. This approach also determines optimal solutions for the power output in various scenarios characteristic and not characteristic of UTEs or power plants, considering changes in active power generation and reducing greenhouse gas emissions as NOx and CO2. To explore the feasibility of the new solution proposed by this theory, it was used as a test system a set of ten (10) generating units for the case study and three sets of generators´ parameters described in the literature. They were used for demonstrating the robustness of the proposed solution considering the use of various deterministic and Bioinspired computing methods for mono-objective and multi-objective optimization. The results presented here, from an analysis of several practical examples show the advantages of the new proposed solution.
Acesso aberto (Open Access)
Previsão multi-passos a frente do preço de energia elétrica de curto prazo no mercado brasileiro
(Universidade Federal do Pará, 2014-11-28) RESTON FILHO, José Carlos; OLIVEIRA, Roberto Célio Limão de; http://lattes.cnpq.br/4497607460894318; AFFONSO, Carolina de Mattos; http://lattes.cnpq.br/2228901515752720
Electricity price forecasting is an important issue to all Market participants in order to decide bidding strategies and to establish bilateral contracts, maximizing their profits and minimizing their risks. Energy price typically exhibits seasonality, high volatility and spikes. Also, energy price is influenced by many factors such as power demand, weather, and fuel price. This work proposes a new hybrid approach for short-term energy price prediction. This approach combines auto-regressive integrated moving average (ARIMA) and neural network (ANN) models in a cascaded structure and uses explanatory variables. A two step procedure is applied. In the first step, the selected explanatory variables are predicted. In the second one, the energy prices are forecasted by using the explanatory variables prediction. The proposed model considers a multi-step ahead price prediction (12 weeks-ahead) and is applied to Brazilian market, which adopts a cost-based centralized dispatch with unique characteristics of price behavior. The results show good ability to predict spikes and satisfactory accuracy according to error measures and tail loss test when compared with traditional techniques. Additionally, is proposed a classifier model consisting of ANN and decision trees in order to explain the rules of price formation and, together with the predictor model, acting as an attractive tool to mitigate the risks of energy trading.
Acesso aberto (Open Access)
Solução para o despacho econômico ambiental de um sistema de geração térmica por recozimento simulado
(Universidade Federal do Pará, 2018-02-27) BRITO JÚNIOR, Jorge de Almeida; NUNES, Marcus Vinícius Alves; http://lattes.cnpq.br/9533143193581447
In recent years, population and government concerns about environmental protection have increased. At the same time, the use of fossil fuels to the production of electricity is still high, due to the high availability of this kind of energy and the consolidated technology of the thermal plants. In that context, it has become increasingly common to adopt methodologies to optimize the operation of thermoelectric plants, not only in terms of fuel costs, but also the emissions of pollutants generated, with a positive impact on the reduction of environmental pollution for electric power generation by thermal systems based on fossil fuels. This process establishes the need for research in the field of energy planning, usually based on the application of optimization methods that consider the two objectives mentioned in an integrated way. Optimization tools based on metaheuristic characteristics, such as simulated annealing, are well suited to these types of problems. In this context, the aim of this PhD thesis was to apply multiobjective optimization in the environmental economic dispatch (DEA) of thermal plants using simulated annealing, comparing the results obtained with other metaheuristic techniques. This tool was used with an aptitude function that involves two objectives (cost and emissions), to find the optimal result, taking into account the shutdown of less efficient engines, thus ensuring the reduction of financial costs and pollution.

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