Artigos em Revistas

Non-Technical Losses (NTL) remain a challenge because electricity theft is prevalent in traditional meters and smart metering systems and structures. They cause financial losses that affect the security of supply and lead to a cooperative burden because NTL are incorporated in the expense tariff and are paid by all customers in countries such as India, China, Brazil, Tunisia, Uruguay, and others. A significant number of methods have been proposed to detect NTL, but they cannot precisely recognize this type of fraud, which enables companies to better identify the fraud’s origin and evaluate its financial impact. In addition, it is important to combine several Time-Series Classification (TSC) algorithms which consider the time-dependent nature of energy consumption data. We propose a data-oriented heterogeneous ensemble predictor based on time series classifiers for NTL detection, called DETECT. It classifies energy consumption samples either as honest or as fraudulent and further categorizes the type of fraud which might have been committed based on the analysis of the consumption patterns of each sample. DETECT is a fraud detection algorithm that has the ability to analyze and classify NTL frauds effectively regardless of the dataset. Using our proposed approach, we obtained a performance improvement with a Detection Rate (DR) value equal to 93.45% and a False Positive Rate (FPR) value equal to 1.61%. DETECT focuses on time-series data, which enables the development of a method that better interprets real-world scenarios and it is more error-resistant.

LUCAS BASTOS, GEAM PFEIFF, RAMON OLIVEIRA, HELDER OLIVEIRA, MARIA EMÍLIA TOSTES, SHERALI ZEADALLY, EDUARDO CERQUEIRA, DENIS ROSÁRIO

A popularização da aquisição de veículos elétricos amplificou-se consideravelmente nos últimos anos, acarretando uma maior necessidade de planejamento do setor elétrico. Desse modo, este artigo visa desenvolver uma metodologia para a análise dos impactos da recarga não controlada de veículos elétricos em redes de baixa tensão, por meio de simulações no software OpenDSS, desenvolvidas com base no método de Monte Carlo, em uma rede de distribuição do município de Belém/PA. Os resultados ressaltam que a inserção massiva não controlada de VE’s na rede de distribuição de baixa tensão pode ocasionar subtensão nas barras e sobrecarga de transformadores, sendo a metodologia apresentada neste artigo capaz de auxiliar na previsão do local em que os problemas ocorrerão.

GABRIEL HENRIQUE SANTOS DE OLIVEIRA, LAURO CORREA DOS SANTOS JUNIOR, JOÃO VICTOR DOS REIS ALVES, MARIA EMÍLIA DE LIMA TOSTES, CARLOS EDUARDO MOREIRA RODRIGUES, KAIO HENRIQUE SINIMBU FORTE, GABRIEL AUGUSTO SILVA COUTO

Among the main problems faced in the context of electric mobility today, the management and monitoring of electric vehicle charging stations, the integration between the diverse types of technologies that make up its architecture, and its low scalability stand out. Therefore, we will present the implementation and complete integration of an electric vehicle charging system in an electric mobility pilot project being executed in the Amazon region in Brazil. Therefore, a literature review of related works will be presented, and its entire implementation will be addressed, from the charging infrastructure, through its back-end system and its Internet of things platform, to its front-end web system for monitoring charging stations. In addition, a complete prototype is created with a real testbed to verify the scalability of the implemented physical system. Based on the testbed evaluations performed, we observe that the implemented system performs well in receiving and sending data from up to 160 electric vehicle charging stations, achieving an average consumption of 26% for CPU and 95% for memory. In addition, it is important to mention that the deployed system supports horizontal scalability, enabling the connection of more charging stations and making it ideal for other integrated systems similar to ours. Based upon the main results obtained with the implemented system, the possibility of carrying out the management and monitoring of charging stations stands out; the integration of different technologies, from the back end and IoT middleware to its front end; a system that supports scalability, enabling the connection of more charging stations; and a reference architecture for charging station management and monitoring systems for the Amazon region.

ELEN LOBATO, LUCAS PRAZERES, IAGO MEDEIROS, FELIPE ARAÚJO, DENIS ROSÁRIO, EDUARDO CERQUEIRA, MARIA TOSTES MARIA TOSTES SCIPROFILESSCILITPREPRINTS.ORGGOOGLE SCHOLAR, UBIRATAN BEZERRA, WELLINGTON FONSECA, ANDRÉIA ANTLOGA

Electric induction motors are the type of motor most commonly operated in industry, and for this reason technologies that predict faults and reduce the corrective maintenance are of great interest. In this context, this paper presents a predictive maintenance tool of electric motors using the concepts of Digital Twin (DT) and Industrial Internet of Things (IIoT). The proposed system is innovative, as it monitors the motor current and temperature by means of sensors and a low-cost acquisition module, and these measurements are sent via Wi-Fi to a database. The concept of DT was leveraged by providing the measurements as inputs to a high-fidelity strongly-coupled model of the monitored monitor, using the Finite Element Method (FEM). The results obtained are satisfactory, because the sensors used presented acceptable errors that do not interfere with the reliability of the results. The computer simulation showed relative errors below 4% in the conductivity analysis and 10% in the temperature analysis. In addition, the simulation allows verifying the internal temperature of the motor, its resistive losses, and the intensity of the magnetic flux at each pole. It is worth pointing out that the internal analysis performed is only possible due to the combination of IIoT and computer simulations. Therefore, they allow a better diagnosis of the motor’s operational status and also a time estimate for the next maintenance service, thus being ideal for the industrial sector.

JHENNIFER F. DOS SANTOS, BENDICT K. TSHOOMBE, LUCAS H. B. SANTOS, RAMON C. F. ARAÚJO, ALLAN R. A. MANITO, WELLINGTON S. FONSECA

The world is experiencing an accelerated energy transition that is driven by the climate goals to be met and that has driven the growth of different potential sectors such as electric mobility powered by electric motors, which continue to be the largest load globally. However, new needs in relation to power density, weight, and efficiency have led manufacturers to experiment with new technologies, such as rare earth elements (REEs). The permanent magnet motor is a candidate to be the substitute for the conventional induction motor considering the new editions of the IEC 60034-30-1, for which study and evaluation continue to be focused on identifying the weaknesses and benefits of its application on a large scale in industry and electric mobility. This work presents a FEM model to assess the line-start permanent magnet motor (LSPMM), aiming to simulate the behavior of the LSPMM under supply conditions with distorted voltages (harmonic content) and evaluate its thermal and magnetic performance. The model created in the FEM software is then validated by bench tests in order to constitute an alternative analysis tool that can be used for studies in previous project phases and even to implement predictive maintenance schemes in industries.

JONATHAN MUÑOZ TABORA, BENDICT KATUKULA TSHOOMBE, WELLINGTON DA SILVA FONSECA, MARIA EMÍLIA DE LIMA TOSTES, EDSON ORTIZ DE MATOS, UBIRATAN HOLANDA BEZERRA, MARCELO DE OLIVEIRA E SILVA

Este artigo apresenta uma análise da rede elétrica do campus Guamá da Universidade Federal do Pará com o objetivo de corrigir o baixo fator de potência que a universidade vem enfrentando desde 2017 e foi agravado pela pandemia de COVID-19. A contribuição deste trabalho é dimensionar um banco de capacitores para realizar a compensação de reativo no campus e consequentemente diminuir as multas referentes ao excedente de reativo.

GABRIEL AUGUSTO SILVA COUTO, BRUNO SANTANA DE ALBUQUERQUE, MARIA EMÍLIA DE LIMA TOSTES, CARMINDA CÉLIA MOURA DE MOURA CARVALHO, UBIRATAN HOLANDA BEZERRA

The Internet of Things (IoT) device scenario has several emerging technologies. Among them, Low-Power Wide-Area Networks (LPWANs) have proven to be efficient connections for smart devices. These devices communicate through gateways that exchange points with the central server. This study proposes an empirical and statistical methodology based on measurements carried out in a typical scenario of Amazonian cities composed of forests and buildings on the Campus of the Federal University of Pará (UFPA) to apply an adjustment to the coefficients in the UFPA propagation model. Furthermore, an Evolutionary Particle Swarm Optimization (EPSO) metaheuristic with multi-objective optimization was applied to maximize the coverage area and minimize the number of gateways to assist in the planning of a LoRa network. The results of simulations using the Monte Carlo method show that the EPSO-based gateway placement optimization methodology can be used to plan future LPWAN networks. As reception sensitivity is a decisive factor in the coverage area, with −108 dBm, the optimal solution determined the use of three gateways to cover the smart campus area.

HUGO A. O. CRUZ, SIDNIR C. B. FERREIRA, JASMINE P. L. ARAÚJO, FABRÍCIO J. B. BARROS, FABRÍCIO S. FARIAS, MIÉRCIO C. A. NETO MIÉRCIO C. A. NETO SCIPROFILESSCILITPREPRINTS.ORGGOOGLE SCHOLAR, MARIA E. L. TOSTES, ANDRÉIA A. NASCIMENTO, GERVÁSIO P. S. CAVALCANTE

O vertiginoso crescimento do uso de veículos elétricos e da instalação de eletropostos cria a necessidade de se pesquisar formas de proteger essas estruturas contra danos provenientes de descargas atmosféricas, principalmente em regiões do planeta onde a ocorrência de descargas atmosféricas é abundante, como na Amazônia. Tais estruturas apresentam inúmeros componentes eletrônicos sensíveis, que podem ser facilmente danificados. Neste trabalho, avalia-se se duas estações de carregamento de veículos elétricos do Centro de Excelência em Eficiência Energética da Amazônia – CEAMAZON – estão adequadamente protegidas contra descargas atmosféricas. Para isso, tomou-se como base os estudos realizados na Ásia, Europa, além da norma brasileira. Constatou-se que, apesar do prédio do CEAMAZON possuir um SPDA adequado, os eletropostos encontram-se vulneráveis, principalmente contra os efeitos indiretos causados pela ocorrência de descargas atmosféricas nas suas proximidades.

IGOR RODRIGUES DE NARDI, ADÔNIS FERREIRA RAIOL LEAL, MARIA EMÍLIA DE LIMA TOSTES, ANDRÉIA ANTLOGA DO NASCIMENTO

O vertiginoso crescimento do uso de veículos elétricos e da instalação de eletropostos cria a necessidade de se pesquisar formas de proteger essas estruturas contra danos provenientes de descargas atmosféricas, principalmente em regiões do planeta onde a ocorrência de descargas atmosféricas é abundante, como na Amazônia. Tais estruturas apresentam inúmeros componentes eletrônicos sensíveis, que podem ser facilmente danificados. Neste trabalho, avalia-se se duas estações de carregamento de veículos elétricos do Centro de Excelência em Eficiência Energética da Amazônia – CEAMAZON – estão adequadamente protegidas contra descargas atmosféricas. Para isso, tomou-se como base os estudos realizados na Ásia, Europa, além da norma brasileira. Constatou-se que, apesar do prédio do CEAMAZON possuir um SPDA adequado, os eletropostos encontram-se vulneráveis, principalmente contra os efeitos indiretos causados pela ocorrência de descargas atmosféricas nas suas proximidades.

IGOR RODRIGUES DE NARDI, ADÔNIS FERREIRA RAIOL LEAL, MARIA EMÍLIA DE LIMA TOSTES, ANDRÉIA ANTLOGA DO NASCIMENTO

The high amount of energy consumption demanded by buildings entails the worsening of several environmental issues. Therefore, actions to make use of this resource more efficient become necessary. The most used methods of Building Energy Modeling (BEM) designated to assess the functionality of such actions are excessively complex and, in many cases, generate unreliable results. Thus, this work aims to elaborate an approach based on Building Information Modeling (BIM) to improve energy efficiency in buildings in a simplified and user-oriented manner. For this purpose, a case study was developed in which two classrooms of an educational building, located in the Amazon region – Brazil, were subjected to three-dimensional modeling and energy simulations in BIM software. In addition to evaluating the classrooms’ current performance regarding daylight, thermal conditions and energy consumption, such simulations intended to assess the implantation of two strategies that sought to reduce energy consumption and maintain thermal and visual comfort by taking advantage of daylight and natural ventilation. Besides of energy saving, such strategies were chosen as they promote Indoor Environmental Quality (IEQ) and help to mitigate the indoor transmission of infectious agents, which is fundamental due to the COVID-19 pandemic scenario, especially in educational environments. The results showed that the strategy based on daylight contribution generated energy savings of around 8% for one of the rooms, and 12% for the other, while the one that exploited the use of natural ventilation was able to reduce energy consumption by about 7% for one of the rooms, and 9% for the other. Therefore, this research presents an important contribution as it provides an intelligible workflow that makes the energy simulation process friendlier and more intuitive and that was able to generate plausible results using BIM-BEM interoperability.

JOÃO GABRIEL CARRIÇO DE LIMA MONTENEGRO DUARTE, BRUNO RAMOS ZEMERO, ANA CAROLINA DIAS BARRETO DE SOUZA, MARIA EMÍLIA DE LIMA TOSTES, UBIRATAN HOLANDA BEZERRA