Programa de Pós-graduação em Engenharia Elétrica e da Computação

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Escalonamento de recursos em redes LTE utilizando processo envelope de tráfego multifractal e curva de serviço mínima
(Universidade Federal de Goiás, 2018-12-14) Abrahão, Diego Cruz; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Sousa, Marcos Antônio de; Lemos, Rodrigo Pinto; Lima, Marcos Antônio Cardoso de; Cardoso, Kleber Vieira
In this work, a variation of the MWM (Multifractal Wavelet Model) model is proposed for network traffic flows, in such a way that its parameters are estimated adaptively. Next, it proposes an envelope process of network traffic based on the parameters' adaptive estimation of this model, whose final objective is to provide quality of service (QoS) in real time. The proposed envelope is compared to the main envelopes processes known in the literature, that are based on traffic models, such as: Brownian Motion (Bm), Fractional Brownian Motion (fBm) and Multifractal Brownian Motion (mBm). This work investigates the use of F-OFDM multi-carrier modulation, which is one of the candidates for 5G networks. It is known that the LTE / LTE-A (Long-Term Evolution) network uses Adaptive Modulation and Coding (AMC) technique that have the function of adjusting the modulation order and code rate based on the user's channel state information, in order to achieve a Block Error Rate (BLER) lesser than 10%. In this work, simulations of the LTE downlink are carried out using OFDM and F-OFDM multicarrier modulation, with the objective of mapping the BLER as a function of SNR (Signal-to-Noise Ratio). This mapping is necessary for the network to adjust the modulation and code scheme appropriate to each user. It's also proposed an adaptive algorithm for resource allocation in the LTE/LTE-A downlink, with admission control of the users. This algorithm aims to improve the performance of some network parameters and to guarantee maximum delay, through of following information: backlog, channel condition and user’s traffic behavior. In order to control the admission of users and to estimate the maximum delay of the network, a minimum adaptive service curve of the LTE / LTE-A network is proposed. The proposed algorithm for resource allocation is compared with several scheduling schemes known in the literature through computational simulations of different LTE network scenarios using OFDM and F-OFDM multi-carrier modulation.
Potencialização do rendimento do gerador a relutância chaveado empregando técnica de rastreamento associada a controle de tensão otimizado
(Universidade Federal de Goiás, 2020-12-16) Araújo, Wanderson Rainer Hilário de; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Coimbra, António Paulo Mendes Breda Dias; Ribeiro, Luiz Eduardo Bento; Sousa, Marcos Antônio de; Oliveira, Marco Antônio Assfalk de; Calixto, Wesley Pacheco
This work presents the potentialization of the efficiency of the Switched Reluctance Generator (GRC) submitted to the control of the output voltage. The efficiency is enhanced by using tracking technique acting on the switching angles of the power converter. As it is a DC machine, the control of the output voltage is applied to adapt this value to DC-AC conversion systems and load controllers. The PID controller is used and, because it is a controller with only one output, other quantities are not contemplated by the performance of the controller. In this work, there is an interest in enhancing the performance of the GRC to make this type of machine more attractive for generating electricity in distributed systems and in installations without connection to the main distribution network. Therefore, in parallel to the PID controller, a tracking technique is applied to the GRC performance with a disturb and observe algorithm. Other procedures are presented, such as obtaining an inductance surface to improve the mathematical and computational modeling of the generator, in addition to the development of an indirect conjugate detection system. Simulation and experimental results are presented for validation and discussion of the proposed study.
Processo de otimização aplicado no projeto térmico e luminoso de luminárias de Led de alta potência
(Universidade Federal de Goiás, 2022-11-25) Barbosa, José Luiz Ferraz; Simon, Daniel John; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Magalhães, Alana da Silva; Reis, Márcio Rodrigues da Cunha; Cruz Junior, Gelson da; Marques, Leonardo Garcia
This work develops an optimization methodology for the design of high power LED luminaires – HP-LED. The objective is to design a luminaire with optimized geometry and LED quantity. The solution to the problem must have an illuminance uniformity factor in the illuminated area according to standards established by regulations and adequate thermal management that guarantees luminous flux and lifetime within the nominal standards established by the HP-LED manufacturer. A computational model of the geometry of the HP-LED luminaire is used, in which thermal and optical analyzes are performed through simulators. Simulation and experimental results are presented for validation of the proposed study and from the results of the simulations a multi-objective evaluation function is developed in order to categorize potentially viable solutions. The optimized solution obtained proposes the design of a rectangular luminaire with an arrangement of 2 × 2 HP-LED with a temperature that reaches a maximum value of 73.9oC in steady state and an illuminance uniformity factor of 0.228 for individual lighting. The illuminance uniformity factor found for two adjacent lighting points on pedestrian paths is 0.5413, with minimum illuminance of 36.95lx, maximum illuminance of 93.65lx and average illuminance of 68.27lx. It is concluded that the metric developed in this proposal is capable of evaluating lighting criteria and nominal criteria of thermal limitation, even managing to classify different types of luminaires.
Controle e estabilização de aeronaves não tripuladas submetidas a falhas nos motores
(Universidade Federal de Goiás, 2024-06-07) Bulhões, Júnio Santos; Magalhães, Alana da Silva; http://lattes.cnpq.br/4812531916179139; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Magalhães, Alana da Silva; Coimbra, Antonio Paulo; Araújo, Wanderson Rainer Hilário de; Martins, Marcella Scoczynski Ribeiro
The objective of this work was to develop a methodology that utilizes control techniques to stabilize unmanned aerial vehicles subjected to engine failures. The methodology includes the creation of a test bench that allows independent rotational movements of ϕ and θ, eliminating translational movements and reducing its interference with the aircraft’s inertia matrix. Control techniques are implemented to stabilize the aircraft in situations of propulsor failure. The experiments demonstrate an improvement in the aircraft’s stability, with a reduction of more than 80% in the effects produced by the failure in the initial moments and the maintenance of stability in scenarios with up to 30% propulsor performance degradation. The proposed method surpasses other approaches in terms of efficiency and preservation of the aircraft’s autonomy. Both the developed test bench and the simulator are validated, and the auxiliary control that operates post-failure is tested in simulation and on the test bench, demonstrating its ability to stabilize the aircraft during failures in one of its propulsors, providing a viable and efficient solution for real-world situations.
Análise e otimização da rede de distribuição de energia utilizando conceitos de redes inteligentes
(Universidade Federal de Goiás, 2021-10-21) Caetano Neto, João; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Reis, Márcio Rodrigues da Cunha; Lemos, Rodrigo Pinto; Marques, Leonardo Garcia; Magalhães, Alana da Silva
The main objective of this work is to develop a methodology for analyzing the quality of the voltage level in the distribution power grid to identify and re-duce the violations of voltage limits through the proposition of optimal points for the allocation of photovoltaic distributed generation. The methodology uses the geographic location of the power grid and its consumers to perform the grouping and classification in spatial grids of 100×100 m using the average annual consumption profile. The generated profiles, including the grid infor-mation, are sent to the photovoltaic distributed generation allocation algo-rithm, which, using an optimization process, identifies the geographic location, the required installed capacity, and the minimum number of photovoltaic gen-eration units that must be inserted to minimize the violations of voltage limits, respecting the necessary restrictions. The entire proposal is applied in a real feeder with thousands of bars, whose model is validated with measurements carried out in the field. Different violations of voltage limits scenarios are used to validate the methodology, obtaining grids with better voltage quality after the optimized allocation of photovoltaic distributed generation. The proposal presents itself as a new tool in the work of adapting the voltage of the distri-bution power grid using photovoltaic distributed generation.
Controle adaptativo de fluxos de tráfego de redes baseado em modelagem multifractal e sistemas fuzzy
(Universidade Federal de Goiás, 2019-08-13) Cardoso, Alisson Assis; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Sousa, Marcos Antônio de; Lemos, Rodrigo Pinto; Vieira, Robson Domingos; Dantas, Maria José Pereira
The network traffic flows that arrive at the base station to be transmitted to the mobile users, in a 5G network system, enter the queuing process until transmission rates are provided. In order to minimize the delay, this work proposes the use of flow control algorithms based on the prediction of user queue behavior. Thus, the more accurate the data prediction, the greater the accuracy and control of flow control algorithms. To improve accuracy, models describing the behavior of network traffic are employed. In this work, two adaptive modeling algorithms based on the Lognormal Beta and BetaMWM models are proposed to model the network traffic and allow its use in real-time applications, such as the 5G network. Simulations are performed in comparisons to multifractal models found in the literature to validate the proposed algorithms, where results in terms of expected value, variance, moments of 2º to 4º order, mean squared errors of autocorrelation and distribution function prove the adaptively use of the algorithms. To perform the flow control, an equation is also proposed to obtain the optimal prediction-based control rate, where generalized ortonormal functions and fuzzy modeling are employed. Simulations of the Downlink 5G link are also performed to validate the proposed flow control algorithms. For this, results in terms of Flow, Utilization, Loss Rate, Delay and Average Waiting Queue are presented, proving the efficiency in the use of multifractal models, orthonormal basis functions, and fuzzy modeling in flow control algorithms for Downlink 5G systems. Taking advantage of the proposed multifractal modeling, an equation is also proposed to estimate the delay limitation for the first recommendations of the 5G network using the network calculation theory. For this, it is proposed a stochastic envelope process for network traffic based on the Adaptive Beta Lognormal model where comparisons with envelope processes known in the literature are performed.
Aplicação da inteligência artificial, ontologia e mineração de dados para classificação de sentenças judiciais
(Universidade Federal de Goiás, 2021-12-20) Castro Junior, Antonio Pires de; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Peretta, Igor Santos; Araújo, Wanderson Rainer Hilário de; Soares, Fabrizzio Alphonsus Alves de Melo Nunes; Gomes, Viviane Margarida; Calixto, Wesley Pacheco
The objective of this work is to apply together ontology with bag-of-words models, similarity learning, and document classification in texts with uttered decisions. The objective is to improve the results of data mining in a database of court decisions. An automatic method of searching sentences in judicial processes related to the one under judgment is developed using the frequency term-inverse of frequency in documents model together with the Jaccard similarity coefficient, establishing weights on the co-occurrence of terms in legal texts of the same category. A dataset with document vectorization is used for supervised training of machine learning algorithms, aiming to classify new justice processes. The proposed methodology provides flexibility to the Judiciary, simulating the role of legal advisors in preparing court decisions with less time and efficiency in the search for jurisprudential standards. The results obtained show that, through accuracy metrics, the proposed model is effective and efficient, and can be applied in the process of identification of court decisions. Thus, the application of artificial intelligence, ontology, and data mining is indicated for information retrieval in court decisions.
Localização em ambiente interno usando a rede celular
(Universidade Federal de Goiás, 2024-07-15) Conceição, Paulo Francisco da; Rocha, Flávio Geraldo Coelho; http://lattes.cnpq.br/5583470206347446; Rocha, Flávio Geraldo Coelho; Vieira, Robson Domingos; Silva, Hugo Vinícius Leão e; Lemos, Rodrigo Pinto; Vieira, Flávio Henrique Teles
In this work, we propose an approach for Simultaneous Localization and Mapping (SLAM) of the Mobile Station (MS) and scatterers (SCs) in indoor environments using the cellular network. The approach, named IndoorLoc, employs a Single bounce scattering model and treats signals as rays, representing each radio frequency signal originating from multiple paths in an indoor environment where reflections occur at SCs. The estimation of the MS and SCs positions involves three main stages: (1) channel modeling, employing millimeter waves (mmWave) and a massive number of antennas (massive MIMO - mMIMO) arranged in a rectangular array; (2) parameter estimation, using an adaptive method based on Compressed Sensing (CS), the Distributed Compressed Sensing Simultaneous Orthogonal Matching Pursuit (DCS-SOMP); and (3) localization of the MS and SCs, applying geometric methods to detect Line of Sight (LoS) and Non-Line of Sight (NLoS) conditions and specific algorithms for each of these conditions. For IndoorLoc, two geometric methods are proposed: one for LoS conditions, which uses Time of Arrival (ToA) and Angle of Departure (AoD) parameters to determine the direction of propagation and the distance between the BS and the MS, and another for NLoS conditions, which uses ToA, AoD, and Angle of Arrival (AoA) to determine intersection points of the trajectories. This intersection point serves as the initial estimate of the MS localization and acts as an input for further refinement using a Gauss-Newton-based estimator, which minimizes the localization error using a nonlinear model derived from the ToA, AoD, and AoA parameters. The performance of the localization algorithms is evaluated through comparisons of the Root Mean Square Error (RMSE) values with existing methods in the literature. Additionally, simulations were conducted in an indoor environment configured according to the specifications of the 3rd Generation Partnership Project (3GPP). The results demonstrate that the accuracy of IndoorLoc meets the standards of the Federal Communications Commission (FCC) and 3GPP.
Contribuições à modelagem, controle e integração de dispositivos fotovoltaicos a sistemas elétricos de potência
(Universidade Federal de Goiás, 2023-11-03) Corrêa, Henrique Pires; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Palhares, Reinaldo Martinez; Kopcak, Igor; Negrete, Lina Paola Garcés; Belchior , Fernando Nunes
The prominence attained by photovoltaic (PV) power generation among the various available renewable energy resources has led to the need of analyzing and engineering such technology at a wide range of implementation scales, beginning from the electrical characteristics of PV cells, passing through the local control of PV generation systems, up to the massive integration of PV resources to wider electrical power systems, such as the distribution grid. This thesis is divided into three parts, each of which presents novel contributions to the study of PV systems in the three aforementioned scales of analysis. In the first part, analytical modeling of PV cell current-voltage (I-V) characteristics by means of explicit closed-form equations is addressed. A new piecewise quadratic model is proposed, which is shown to perform either better or comparably, for different solar cells, to state-of-the-art models in terms of accuracy. Two methods are established for computing the model parameters: the first one is analytical and only requires datasheet information, whereas the second one uses linear-complexity optimization with respect to I-V samples in order to further improve accuracy. In the second part, the problem of maximum power point tracking (MPPT) in two-stage PV systems is considered. First, a new hybrid MPPT method which uses direct duty cycle control for enhanced tracking efficiency is developed for grid-tied systems. Then, an analytical MPPT approach for single-phase off-grid variable-voltage systems is presented and subsequently generalized to consider current harmonics and three-phase loads. Both proposed MPPT methods are shown, by means of simulation, to perform better than existing methods with similar implementation complexities. In the third part, voltage control of distribution systems with photovoltaic penetration by means of PV inverter reactive power support is studied. Three novel decentralized methods for controlling the inverter reactive power setpoints are proposed. The first method considers voltage measurements are available at each PV inverter and consists in the heuristic specification of a cooperative decentralized Markov decision process (MDP), whose offline solution yields voltage control policies to be carried out by the grid zone controllers. On the other hand, the second method assumes voltage measurement and computational resources are scarce and establishes a decentralized strategy which only uses two voltage measurements per control zone and is directly compatible with droop-type controls usually found in PV inverters. At last, a third method is presented which combines cooperative MDP, droop control and a switching mechanism for achieving a compromise between voltage regulation and reduction of active power losses. All methods are compared to similar existing approaches, via simulations with real irradiance profiles in a large distribution grid, yielding favorable performances.
Análise de viabilidade técnica, econômica e ambiental de um projeto de eficiência energética associado com geração distribuída
(Universidade Federal de Goiás, 2022-04-25) Faria, Adriano Ferreira de; Marra, Enes Gonçalves; http://lattes.cnpq.br/8463332056679918; Alvarenga, Bernardo Pinheiro de; http://lattes.cnpq.br/9850449311607643; Alvarenga, Bernardo Pinheiro de; Marra, Enes Gonçalves; Belchior, Fernando Nunes; Viajante, Ghunter Paulo; Domingos, José Luis
This study focused on developing a sustainability project carried out in 11 Federal Institute of Education, Science, and Technology of Goiás (IFG) campuses, combining energy efficiency and distributed generation actions to optimize energy consumption by through the retrofit of the lighting system, installation of a photovoltaic generation system, energy monitoring, and qualification and training of teachers, students and employees, in compliance with the guidelines established by the National Electric Energy Agency (ANEEL) within the scope of the Public Call for Priority Projects for EE and Strategic R&D nº 01/2016 – “Energy Efficiency and Mini Generation in Public Institutions of Higher Education”. In the lighting system, 18,377 inefficient lamps were replaced by lamps with more efficient technology, with an energy saving of 867.9 MWh/year and a peak demand reduction of 309.6 kW. The proposed generation system aimed to install 3076 PV modules on the rooftops of selected campus buildings, totaling 1 MWp of installed power with an average annual power generation of 1736.9 MWh/year. The total project investment was USD 1,348,768.50 and the global cost–benefit ratio of the project was 0.68, which will result in annual savings of approximately USD 197,321.85. This corresponded to a 58% reduction in energy bills. The project proposed in this work was considered technically and economically viable within the scope of the Brazilian Energy. The estimate of avoided carbon emissions is also carried out, considering the methodologies used by the United Nations Framework Climate Change Convention (UNFCCC) for Clean Development Mechanism (CDM) projects that include energy efficiency activities and grid-connected renewable energy generation, resulting in an avoided emission of 983.36 tCO2 eq.
Detecção de imagens falsificadas baseada em descritores locais de textura e rede neural convolucional
(Universidade Federal de Goiás, 2020-06-30) Ferreira, William Divino; Soares, Fabrizzio Alphonsus Alves de Melo Nunes; http://lattes.cnpq.br/7206645857721831; Cruz Júnior, Gélson da; http://lattes.cnpq.br/4370555454162131; Cruz Júnior, Gélson da; Pedrini, Hélio; Salvini, Rogério Lopes; Costa, Ronaldo Martins da; Lemos, Rodrigo Pinto
Nowadays, digital image transformation has become a widespread activity. Hence, image copying, cloning, and resizing are easily performed, making it challenging to check image integrity and authenticity. Moreover, a criminal investigation from digital images becomes extremely hard, because using those images as proof demands to ensure its legitimately,under a risk to implicate the whole legal process.In this sense, this work develops a model for forged images based on local texture descriptors with convolutional neural networks. Henceforth, in this work, firstly, we evaluated fourteen local texture descriptors in five public image texture datasets, and then we selected descriptors with the best efficacy. Second, the selected descriptors are applied to four public datasets to extract texture features from forged and legit images. Finally, those features are used to train a residual convolutional neural network, and then, classifying images as authentic or forged with a Support Vector Machine Classifier. A result of the proposed model provides enthusiasm, mainly when applied to a dataset with a small number of images.
Modelos de simulação e controle preditivo generalizado de sistemas fotovoltaicos conectados à rede
(Universidade Federal de Goiás, 2019-11-28) Franco, Ricardo Augusto Pereira; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Negrete, Lina Paola Garces; Castro, Marcelo Stehling de; Soares, Telma Worle Lima; Belchior, Fernando Nunes
After the Second Industrial Revolution, the electric energy became an essential item for the world population. Beyond the environmental impacts caused by polluting energy sources, the awareness of clean energy generation has been growing worldwide. In this way, renewable and clean energy sources gain prominence in relation to traditional dirty energy sources. Photovoltaic systems can help to reduce the energy consumption at the consumer units in which they are deployed and it can contribute to reducing the energy demand provided by the utility power grid. Thus, the objective of this work is to provide modeling, simulation and control methods for photovoltaic systems in order to assist the photovoltaic systems projects, to analyze the quality of the energy produced, the impacts that these systems cause on the distribution network and to perform the control of power generation of photovoltaic systems. It is proposed to develop optimization and analytical methods for the estimation of the parameters of the single diode model. The estimation of the parameters is performed to improve the modeling of a photovoltaic module and, consequently, its performance in the generation of energy. Then, simulations of grid-connected photovoltaic systems are proposed with the purpose of analyzing the impacts that the photovoltaic energy generation implies on the consumer loads and on the distribution network. Finally, it is proposed a method of energy flow control in a system consisting of photovoltaic system and energy storage system, in order to reduce the energy consumed from the utility grid. The energy flows in this electric system with energy storage system (hybrid system) can be combined to provide power for a load or inject power into the distribution network. The results presented show the benefits of the estimation of parameters of a photovoltaic module in terms of power generation. The results of the simulations show the impacts of photovoltaic systems for the consumer who installed the system and for the utility to design its energy distribution networks in medium and long-term. The results of the controller present the optimization achieved through the control of hybrid energy systems, reducing the costs of the energy consumption of a load and making the most efficient use of the energy storage system.
Acústica aplicada no desenvolvimento de equipamentos para agricultura de precisão
(Universidade Federal de Goiás, 2022-07-08) Furriel, Geovanne Pereira; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Silva, José Geraldo da; Araújo, Wanderson Rainer Hilário de; Jakelaitis, Adriano; Cruz Junior, Gelson da
This work presents methodology for development of precision agriculture equipment based on acoustic and vibration techniques. The proposed methodology uses the scale reduction method to simulate the induced vibration and the direction of sound pressure fields. After analyzing the scale-down model, the prototype is built in real dimensions to validate the proposed system. Two acoustic induction systems are designed and evaluated, one for applying phytosanitary products and the other for selective fruit harvesting. When applying the phytosanitary product, there is a reduction in drift and an increase in leaf coverage by approximately 45%. In the selective harvest, the proposed method is analyzed, and approximately 40% of the fruits were harvested at the appropriate maturation stage. The acoustic techniques presented applied to agriculture are promising for developing equipment for handling and harvesting in precision coffee farming. The results indicate that using acoustic techniques promotes the reduction of the inherent wear of the harvest in the plants.
Estudo, implementação e otimização de técnicas de controle avançado
(Universidade Federal de Goiás, 2022-10-06) Ganzaroli, Cleber Asmar; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Magalhães, Alana da Silva; Calixto, Wesley Pacheco; Gomide, Renato de Sousa; Lemos, Rodrigo Pinto; Araújo, Wanderson Rainer Hilário de
This work proposes the tuning, implementation, analysis and comparison of different control strategies applied to the same system. The controllers studied are: Proportional, Integral and Derivative, Nonlinear Predictive, Fuzzy Control and Sliding Mode Control. These techniques are applied to the speed control of an independently excited DC motor driven by a fully controlled three-phase rectifier. The methodology proposes the bench design, the modeling of the real system by the system identification method, the sensitivity analysis and the adjustments of the controllers parameters using an optimization process. Comparisons are made between the techniques, highlighting their characteristics and performance considering similar conditions of execution. The robustness of each control when acting on a non-linear system is investigated. All control techniques are applied in three different tests: i) step-type reference signal, without load application, ii) reference signal with amplitude variation, without load application and iii) step-type reference signal, with load application. The techniques present satisfactory performance in the execution of the proposed control, depending, therefore, on the analysis of the system to be implemented to determine the appropriate method.
Complexidade natural de sistemas com base em análise de sensibilidade
(Universidade Federal de Goiás, 2020-09-30) Gomes, Viviane Margarida; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Wainer, Gabriel Andres; Peretta, Igor Santos; Pinheiro Neto, Daywes; Martins, Weber
This work proposes a methodology for analyzing systems based on a particular measure of complexity, called the natural complexity of the system. This measure corresponds to the proper level of complexity of each system, characterized by the region of optimized configurations. Given the optimal or optimized solution, the sensitivity analysis is performed to define the impact generated at the output of the system due to variations in the input parameters. The proposed methodology comprises: i) sensitivity analysis metrics, ii) system complexity metrics based on weighted connections, iii) analysis of the system using natural complexity as a reference and iv) development of models for application of the methodology. The complexity metric uses the sensitivity indices of the parameters to define the relevance values of the connections, in order to establish a relationship between the parties and the whole. The results point to the complexity metric as a mechanism for synthesizing the configuration, arrangement, performance and workload of the system in a single measure. Regarding the measure of natural complexity, it may be used as a reference of the desired level of complexity, since it was significantly different from the measures obtained under overload or idle conditions. Thus the natural complexity may correspond to the minimum complexity value of the system in regular activity. The proposed complexity metric strengthened the assertion that every system exhibits some level of complexity. Thus, it may be said that complexity is the totality of the system in interaction, with its own internal dynamics and its own environmental flows.
Otimização da força contra eletromotriz e do torque eletromagnético mediante a modificações nos parâmetros estruturais de uma máquina síncrona de ímãs permanentes
(Universidade Federal de Goiás, 2021-08-02) Jesus, Luiz Henrique Reis de; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Paula, Geyverson Teixeira de; http://lattes.cnpq.br/0140145167826333; Paula, Geyverson Teixeira de; Pereira, William César de Andrade; Almeida, Thales Eugenio Portes de; Suetake, Marcelo; Brito, Leonardo da Cunha
This work aims to present an approach to the optimization process of a surface mounted permanent magnet synchronous machine (SM-PMSM) using the Tensors method, as well as methods and techniques for parametric optimization and topological optimization. It evaluates the behavior of the Back-Electromotive Force (Back-EMF) operating at no load and under load, as well as the behavior of the electromagnetic torque. The optimized parameters directly relate to the saturation of the machine as the electromagnetic load is increased (nominal load). The optimization process allows a reduction in the electromagnetic torque ripple, keeping the back-electromotive force unchanged. The results for the optimization of the Back-Electromotive Force presented variations lower than 0,5% when compared to its behavior operating at no load, with its behavior operating under load. For the electromagnetic torque optimization process, the results achieved provided to the SM-PMSM project a reduction in the electromagnetic torque ripple of approximately 37% and a reduction in the structural volume of 38,23%. Finally, optimization techniques and methodologies were compared regarding the results and objectives proposed for the optimization of the permanent magnet synchronous machine under study.
Development and analysis of mathematical methods for estimating statistical parameters in sensor array-based systems
(Universidade Federal de Goiás, 2020-02-07) Kunzler, Jonas Augusto; Sander, Oliver; Lemos, Rodrigo Pinto; lattes.cnpq.br/3333000136853156; Lemos, Rodrigo Pinto; Sander, Oliver; Fleury, Claudio Afonso; Vieira, Robson Domingos; Castro, Marcelo Stehling de
A estimação da direção de chegada e a estimação de pulsos de energia na espectroscopia de raios-x são baseadas no mesmo parâmetro, o deslocamento de fase de sinais em relação a uma referência. Neste trabalho é demonstrada a possibilidade de aplicar técnicas já estabelecidas para a estimação da direção de chegada ao problema de espectroscopia. Os dois temas são correlacionados em uma parte introdutória e em seguida eles são discutidos separadamente dando ênfase nas características intrínsecas de cada um. No problema de estimação da direção de chegada, inicialmente apresenta-se o modelo de sinal para o arranjo de sensores e alguns métodos baseados no estimador de máxima verossimilhança. Considerando um arranjo de sensores linearmente distribuídos e com espaçamento uniforme entre os elementos, os sinais induzidos em cada circuito serão cópias defasadas de um sinal de referência. O defasamento está intimamente relacionado com a direção de chegada. No domínio espacial, as direções de chegada representam frequências de funções exponenciais complexas, as quais deverão ser estimadas. Os principais métodos de estimação são o MODE, MODEX, o MODEX modificado, e o SEAD. Atenção especial é dispensada ao método SEAD que é baseado na decomposição em autovalores da matriz de correlação espacial modificada. A diferença entre os dois maiores autovalores gera uma curva com picos proeminentes indicando as direções de chegada de ondas planas. A esta curva dá-se o nome de espectro diferencial. Uma análise matemática do espectro diferencial, denominada de espectro diferencial total, é desenvolvida e demonstra-se que a norma matricial induzida pela norma-2 vetorial é a principal componente do cálculo. Portanto, propõe-se uma abordagem baseada em normas matriciais para a estimação das direções de chegada. Uma descrição matemática geral foi desenvolvida, a qual explicita a relação entre os verdadeiros ângulos de chegada e um ângulo sintético usado para varrer todo o espectro, a correlação entre as fontes, o número de fontes e o número de sensores. Demonstra-se que a diferença entre os ângulos determina a amplitude do pico gerado. A formulação matemática do espectro angular constitui em uma das principais contribuições deste trabalho, porém, outros aprimoramentos foram alcançados através da proposta de uso de normas matriciais. A utilização da abordagem baseada em normas evita a necessidade de realização da decomposição da matriz em autovalores e, consequentemente, o tempo de execução total do método é reduzido e o erro quadrático médio é reduzido para situação de fontes afastadas. Comparando as propostas com os métodos estabelecidos na literatura, a abordagem de normas supera o método MODE e seus derivados com relação ao erro quadrático médio. Porém, com relação ao tempo de execução os métodos baseados no SEAD são mais custosos computacionalmente para um número de fontes menor do que 4. A estimação de pulsos de energia na espectroscopia de raios-x não é um tema novo, porém, o multiplexador SQUID de micro-ondas é uma abordagem relativamente nova e, atualmente, ele consiste em um tema de pesquisa pujante. O objetivo do sistema é estimar a energia de partículas energéticas que incidem em detectores, os quais podem ser do tipo transition edge sensor ou metallic magnetic calorimeters. Os calorímetros metálicos são sensores paramagnéticos que estão situados em um campo magnético fraco, eles traduzem variação de temperatura em variação de fluxo magnético. Para realizar a leitura das variação de fluxo magnético decorrente da incidência de partículas emprega-se um componente supercondutor denominado de superconducting quantum interference device (SQUID). O SQUID é um interferômetro de extrema sensibilidade e se comporta como um indutor variável. O SQUID é acoplado a uma terminação de uma linha de transmissão supercondutora e produz alterações na frequência de ressonância do circuito. Portanto, a energia de partículas pode ser lida eletronicamente através da demodulação de uma onda de rádio que percorre o ressonador. A modulação ocorre na amplitude e fase de uma portadora complexa. Após a exclusão de frequências intermediárias, resultado do processo de mixagem da portadora, obtem-se uma portadora complexa de frequência baixa sobre a qual métodos de estimação de fase são aplicados. Pela semelhança com o problema de estimação da direção de chegada, propõe-se uma abordagem baseada em arranjo de sensores e decomposição da matriz de correlação espacial em autovalores. Desta forma, estabelece-se uma analogia entre os dois problemas. Para a obtenção da matriz de correlação, considera-se a existência de um vetor de referência cuja fase não depende da incidência de partículas, i.e., quando o sistema está em repouso. Este vetor de referência é comparado por meio da função de correlação com os dados que são recebidos a cada instante. Define-se um comprimento do vetor de dados que seja conveniente e, desta forma, obtem-se uma matriz de snapshots com dois sensores e uma matriz de correlação de dimensões 2 × 2. A decomposição em autovalores pode ser resolvida explicitamente em função das entradas da matriz, de tal maneira, que uma formulação geral para o método é apresentada. Além disso, simplificações podem ser impostas com o objetivo de implementação em hardware dedicado. O erro de estimação é analisado para o método proposto e o método de máxima verossimilhança. O método de autovalores apresentou maior robustez ao ruído e em algumas circunstâncias consegue resolver o problema de estimação sem artifícios externos, algo que não ocorre para o método de máxima verossimilhança.
Controle de potência reativa para adequação de valores de tensão e redução de perdas em redes elétricas com geração distribuída fotovoltaica
(Universidade Federal de Goiás, 2024-05-06) Lopes Filho, Gilberto; Vieira, Flávio Henrique Teles; http://lattes.cnpq.br/0920629723928382; Vieira, Flávio Henrique Teles; Negrete, Lina Paola Garces; Corrêa, Henrique Pires; Franco, Ricardo Augusto Pereira; Souza, Gustavo Souto de Sá e
This work presents contributions aimed at improving the electrical voltage profile in compliance with regulatory standards and reducing or minimizing losses in a radial electrical network with distributed photovoltaic generation. By injecting reactive power in a controlled manner through inverters connecting their respective photovoltaic generators to the distribution network buses, it is possible to control network voltages and losses. This work proposes three distinct approaches. The first algorithm, based on observations of the electrical network’s behavior, determines generated reactive power values capable of reducing electrical losses and regulating voltage for various levels of distributed generation penetration and load power factor. The allocation of photovoltaic generators and power values is randomly generated, and through a Monte Carlo simulation, the performance of the proposal can be analyzed. The second proposal uses heuristic algorithms (Genetic Algorithm and Firefly Algorithm) to estimate optimal reactive power values at the buses, aiming at voltage regulation, minimization of electrical losses, or minimization of losses with constraints on voltage magnitude values. The third proposal employs analytical relationships between reactive power, power loss, and voltage deviation to control reactive power injections into the electrical network. These analytical relationships, derived from the equations in this work, ensure computational simplicity while optimizing loss reduction and voltage deviation. This proposal includes the Loss Reduction Algorithm (LRA) and the Voltage Regulation Algorithm (VRA) and introduces an approach to efficiently switch between them called the Combined Control Strategy (CCS). The CCS seeks to provide a balance between voltage regulation and the reduction of electrical losses. Computational simulations are conducted to validate and analyze the performance of each proposal, varying various parameters of the algorithms and the network. All such Proposals are compared with other methods described in the literature, highlighting the superiority of the contributions presented in this work
Repotencialização na operação paralela de gerador síncrono com gerador de indução
(Universidade Federal de Goiás, 2020-03-27) Magalhães, Alana da Silva; Alves, Ayton José; http://lattes.cnpq.br/2762752291082988; Calixto, Wesley Pacheco; http://lattes.cnpq.br/9073478192027867; Calixto, Wesley Pacheco; Alves, Aylton José; Wainer, Gabriel Andrés; Rodrigues, Clóves Gonçalves; Lemos, Rodrigo Pinto
This work presents the comparison between simulation and experimental tests of the repowering system to validate the electrical interactions between an induction generator and a synchronous generator. Parametric regression and optimization models are used to find the constructive parameters of the machines. Two generators are connected to a common bus in steady state, subject to non-linear loads. The results comparing modeling and experimental tests show that the induction generator besides the active power increasing, has a better way for harmonic currents flowing in common bus. It is concluded that the parametric regression has the advantages of not needing to know the parameters provided by the machine's manufacturers and does not need to perform destructive tests and that the induction generator repowering and attenuates current harmonic components present at the connection point, improving the network voltage profile.
Diagnóstico otimizado de transformadores de potência mediante a integração de técnicas preditivas
(Universidade Federal de Goiás, 2018-02-22) Marques, André Pereira; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Ribeiro, Cacilda de Jesus; http://lattes.cnpq.br/8998911644222586; Ribeiro, Cacilda de Jesus; Brito, Leonardo da Cunha; Domingues, Elder Geraldo; Rocha, Adson Silva; Arruda, Colemar
The effective application of predictive maintenance techniques for power transformers is essential for the early detection of defects and failures, and in order to trigger scheduled preventive or corrective actions. This precludes the need for urgent and/or emergency interventions, aiming to reduce unscheduled power outages, which are usually more costly and cause great inconvenience to consumers and the electric power system. In this context, this work focuses on the development of an optimized diagnostic methodology for power transformers, by integrating eleven predictive techniques (with 27 quantities). These techniques are analyzed with respect to voltage level, type of electrical connection and age of the transformers – when applicable –, based on the experience of specialists/analysts, on standards and technical guidelines, and on statistical analyses of a database of actual field and laboratory tests. The analyses of the validation of the results are significant and presented through a specialized system, demonstrating their practical application. The novelty of this thesis consists in the development of an original classification method, called Normalized Doubly Weighted Sum (NDWS), and in the detailed description of the predictive techniques that are integrated, their functionalities, the creation of equations, the definition of criteria and parameters, with their weights and scores for the classification of “A” (excellent) to “E” (very poor), and recommended actions aimed at underpinning decision- making, thereby contributing to the body of studies in this field. Hence, it can be concluded that this work offers a comprehensive and efficient tool to aid in the optimized diagnosis of power transformers, insulated with kraft paper and immersed in mineral insulating oil, providing effective diagnostics and maintenance of these devices, and thus increasing the reliability of electric power systems.

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