Programa de Pós-graduação em Engenharia Elétrica e da Computação
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Navegando Programa de Pós-graduação em Engenharia Elétrica e da Computação por Por Unidade Acadêmica "Escola de Engenharia Elétrica, Mecânica e de Computação - EMC (RMG)"
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Item 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 NunesThe 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.Item Sistema de comunicação alternativa para pessoas com distúrbios neuromotores severos usando redes neurais artificiais(Universidade Federal de Goiás, 2024-12-15) Floriano, Carolina de Souza; Silva, Adson Rocha; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Brito, Leonardo da Cunha; Rocha, Adson Silva; Gomide, Renato de SousaCommunication difficulties are frequent for many people with severe motor disabilities, making it difficult for them to interact with their families, caregivers and society in general. Augmentative and Alternative Communication (AAC) then aims to compensate for the communication deficit of these people, providing the individual with a better quality of life. However, these individuals with severe neuromotor disorders who have severe movement restrictions find great challenges in the use of several current assistive technologies. In this context, the objective of this research is to present an Alternative Communication System based on Artificial Neural Networks with a user-centered approach and their needs, for use by this public. The input and signal processing are carried out by reading facial landmark points, using the MediaPipe FaceMesh library. The development of the gesture/facial expression classifier is performed through the implementation and comparison of two different models: a Convolutional Neural Network (CNN) model and a Recurrent Neural Network model using Long Short-Term Memory (LSTM) units and dense layers. Dynamic challenges were implemented to conduct a more in-depth analysis of the models’ performance in various contexts, varying parameters such as the quantity of samples and the inclusion of similar gestures. Real-time overall results indicate a consistent performance of the proposed system, suggesting that, in both approaches, the Convolutional Neural Network (CNN) stands out significantly compared to the Long Short-Term Memory Recurrent Neural Network (LSTM) in gesture recognition.Item Sistema de comunicação alternativa para pessoas com distúrbios neuromotores severos usando redes neurais artificiais(Universidade Federal de Goiás, 2023-12-15) Floriano, Carolina Souza; Silva, Adson Rocha; http://lattes.cnpq.br/4116708456419800; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Brito, Leonardo da Cunha; Gomide, Renato de Sousa; Rocha, Adson SilvaCommunication difficulties are frequent for many people with severe motor disabilities, making it difficult for them to interact with their families, caregivers and society in general. Augmentative and Alternative Communication (AAC) then aims to compensate for the communication deficit of these people, providing the individual with a better quality of life. However, these individuals with severe neuromotor disorders who have severe movement restrictions find great challenges in the use of several current assistive technologies. In this context, the objective of this research is to present an Alternative Communication System based on Artificial Neural Networks with a user-centered approach and their needs, for use by this public. The input and signal processing are carried out by reading facial landmark points, using the MediaPipe FaceMesh library. The development of the gesture/facial expression classifier is performed through the implementation and comparison of two different models: a Convolutional Neural Network (CNN) model and a Recurrent Neural Network model using Long Short-Term Memory (LSTM) units and dense layers. Dynamic challenges were implemented to conduct a more in-depth analysis of the models’ performance in various contexts, varying parameters such as the quantity of samples and the inclusion of similar gestures. Real-time overall results indicate a consistent performance of the proposed system, suggesting that, in both approaches, the Convolutional Neural Network (CNN) stands out significantly compared to the Long Short-Term Memory Recurrent Neural Network (LSTM) in gesture recognition.Item 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 eThis 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 workItem Minimização da ondulação de torque em motores a relutância variável por meio de correntes de fase de referência otimizadas por algoritmo genético(Universidade Federal de Goiás, 2023-12-18) Soares, Israel Rodrigues; Paula, Geyverson Teixeira de; http://lattes.cnpq.br/0140145167826333; Paula, Geyverson Teixeira de; Oliveira, Eduardo Sylvestre Lopes de; Almeida, Thales Eugenio Portes deThis work proposes an innovative control strategy for the Switched Reluctance Motor with the aim of minimizing torque ripple. The strategy is based on an algorithm for generating current profiles that prioritize the smooth commutation mode of the asymmetric half-bridge converter. This algorithm employs genetic algorithms to calculate these profiles through simulations in a finite element model developed based on a 6x4 Switched Reluctance Motor from the Laboratório de Ensaios de Pequenos Motores at the Universidade Federal de Goiás. To enhance the adaptability of the proposed control, the addition of a compensation derived from torque error to these profiles has been suggested. Simulations compared the Proposed Control with Direct Instantaneous Torque Control and the Proposed Control without the addition of compensation under various operating conditions. The results highlight significant average reductions in metrics used to evaluate torque ripple. In the Torque Ripple metric, there was an average reduction of 16.02% compared to Direct Instantaneous Torque Control and 13.14% compared to the Proposed Control without compensation. As for the Torque Ripple Factor metric, this reduction was 15.34% and 15.96%, respectively. The study concludes by affirming the good performance of the generated current profiles, demonstrating that the inclusion of compensation derived from torque error in these profiles was crucial for the low levels of torque ripple achieved by the proposed control technique.Item Aplicação da transformada de Hilbert-Huang e da seleção paraconsistente de características no campo da entomologia agrícola: uma abordagem para identificação e estimativa de densidade de cigarras em lavouras cafeeiras(Universidade Federal de Goiás, 2023-12-01) Souza, Uender Barbosa de; Escola, João Paulo Lemos; http://lattes.cnpq.br/5894769490673984; Brito, Leonardo da Cunha; http://lattes.cnpq.br/6660680440182900; Brito, Leonardo da Cunha; Vieira, Flávio Henrique Teles; Lemos, Rodrigo Pinto; Escola, João Paulo Lemos; Maccagnan, Douglas Henrique BotturaThe sounds emitted by various insect species carry specific and reliable acoustic characteristics. For this reason, acoustic identification of insects has been widely investigated by the scientific community in the field of pattern recognition. In Brazil, the cicada species Quesada gigas is considered a pest in coffee crops due to its sap-feeding habits, which can cause losses to farmers during intense attacks. Given this scenario, and considering the fact that the most striking characteristic of cicadas is sound emission for reproductive purposes, this work proposes a system designed to assist in the management of pest insects in coffee crops. Specifically, this system aims to detect the presence of cicadas or estimate their density through acoustic signals. The approach innovatively combines the extraction and analysis/selection of sound features through the Hilbert-Huang Transform (HHT) and Paraconsistent Feature Engineering, two emerging methods of growing interest in the scientific community. A detailed study was conducted on the influence of eight stopping criteria for the Empirical Mode Decomposition, the first step of HHT, considering variations of parameters, temporality, signal sampling, and also the encoding of these signals in two formats. The first defines vectors by the energies of the Intrinsic Mode Functions (IMFs) in order of extraction, while the second distributes the energies of the IMFs according to the 25 frequency bands of the Bark Scale. Additionally, the dimensional variation of the vectors was analyzed. The experiments allowed determining low computational cost configurations, showcasing the efficacy of the proposed system, with models based on Support Vector Machines achieving accuracies above 98% in both identification and density estimation of cicadas. Thus, this document details the theoretical foundations, design, development of the system, discussions about possibilities for its practical application, and an initial analysis of a developed application for smartphones. This proposal has the potential to encourage the reuse of old electronic equipment, promoting sustainable and economically viable practices.