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.

O consumo de energia elétrica de forma sustentável tem sido discutido nas últimas décadas a fim de encontrar soluções para a redução de custos e de desperdícios. Para isto, surgem ações de otimização e maior aproveitamento de energia nas edificações uma vez que, as mesmas, são responsáveis por grande parte do consumo. Devido a este cenário, várias metodologias de análise de eficiência energética têm surgido buscando viabilizar essa redução na matriz energética. Este artigo pretende comparar os resultados da Análise de Eficiência Energética do prédio do CEAMAZON realizada através do RTQC, com os resultados obtidos a partir da planilha da Chamada Pública de Projetos (CPP) que utiliza como base de cálculo o PROPEE. O propósito é comparar se os resultados obtidos de ambas as metodologias são próximos. Cabe ainda, pontuar as divergências e aplicabilidades de cada uma.

Energy losses are a fundamental issue in the electricity distribution sector, being an inevitable consequence of transporting energy from supplying sources to consumers’ installations and are becoming one of the factors to be considered in planning and operation of electrical distribution networks. So, electrical distribution losses must be continuously monitored so that they are kept within acceptable levels to ensure the business profitability as well as the good power quality of supplied energy. In this context, this work introduces a modified methodology for technical losses calculation with the application of the concept of reduced equivalent networks, via definition of an Equivalent Operational Impedance, taking as a starting point the electrical network modeling in the Open Distribution System Simulator (OpenDSS). The losses calculation also considers customer’s energy billing measurement data, measurements of injected energy and power factor at the feeder’s coupling bus at the substation, also considering measurement campaigns to characterize the load consumption profiles for working days, Saturdays and Sundays. The proposed methodology disaggregates energy injections in billed energy, technical and non-technical losses parcels, and presents, as the results have demonstrated, a good precision in the proposed calculation procedures.

O presente trabalho propõe formas de melhorar o desempenho energético de edifícios, tendo como estudo de caso um edifício educacional localizado em uma universidade da região amazônica, no qual duas salas de aula foram submetidas numa modelagem tridimensional e em simulações energéticas, utilizando um software que contém tecnologia BIM (Building Information Modeling). Tais simulações buscaram avaliar o desempenho atual das salas no que diz respeito às condições de luz natural e ao consumo de energia. Diante desse diagnóstico, por meio da estratégia de utilização da iluminação artificial como suplemento da luz natural, foi possível gerar economia de energia de cerca de 8% para uma das salas, e 13% para a outras. Portanto, foi possível verificar o sucesso da estratégia mencionada no processo de otimização do conforto visual e da eficiência energética.

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.

The growth in global electricity demand has expanded the search for new energy resources. Renewable sources such as photovoltaic (PV) systems have proven to be major alternatives. PV generators connected to distribution grids have exhibited significant growth in the last decade, so it is essential to analyse the impacts resulting from this increase. This work investigated the influence of high PV system penetration in distribution grids in terms of harmonic levels. In particular, this study addressed the distortions in voltage and current waveforms in the presence and absence of PV generators connected to a distribution grid. Additionally, the total harmonic content and the individual harmonic frequencies of voltage and current were analysed. This study was performed with an IEEE 37 bus distribution system and the Open Distribution System Simulator software (OpenDSS). The results show that the voltage limits of some phases far away from a substation can exceed the limits. Furthermore, the total harmonic distortion (THD) and individual harmonic distortion (IHD) levels for voltage and current were significantly high for harmonics of the 3rd, 5th, and 7th orders, where current levels violate the standard levels.

Photovoltaic systems can strengthen the energy matrix aiming at energy sustainability, however, their intermittence, the availability time frame and seasonality effects are complicating aspects for the operation of these systems. To mitigate such problems, a possible measure is the operation of hybrid systems (HS) associated with storage systems to meet the energy demand. This study presents real operational scenarios for the management of a hybrid mini-grid installed in the Amazon region in Brazil, capable of managing energy supply and demand, changing the generation curve, reducing fossil fuel consumption and energy costs, in addition to providing flexibility and operational safety to the electrical operating under on-grid or off-grid conditions. Through technical and economic analyses, the objective of this study is to show that hybrid systems can be implemented in small and medium consumers, in addition to generating a new market option for utilities. This research evaluates the operation of HS concurrently with the electrical grid and the results show that the system meets the technical requirements, in addition to bringing financial and ecological benefits. This information can support the decisions of consumers, utilities and energy operators for the development of the national market for on-grid and off-grid HS.

The search for more competitive equipment in the global market has led to the implementation of new materials and technologies in the search for greater energy efficiency. This is certainly a guideline followed by the electric motor industry that has introduced new technologies in rotating machines, such as the permanent magnet motor, evolving into increasingly efficient motor classes. However, subjecting these efficient motors under nonideal electric grid power conditions, such as voltage unbalance, can cause these efficient machines to generate additional distortions in the voltage and current waveforms, which in turn not only affect the performance of electric motors themselves but also that of the electrical system in general. This work presents a comparison between energy efficiency gain and the corresponding power quality degradation through a detailed harmonic analysis of the effects of voltage harmonics and voltage unbalance in three 0.75-kW electric motors classes: IE2, IE3, and IE4, The results show that for increasing percentages of a specific harmonic distortion, other harmonics are also increased in the higher efficiency electric motors sample analyzed, and similar responses were also observed for large percentages of voltage unbalance, mainly in the line-start permanent magnet motor class IE4. The results achieved are interesting but rigorously reflect only the tested motor sample and cannot be generalized to all motors, in other power ranges, of the respective motor classes tested. For generalization, exhaustive tests must be accomplished to formulate general conclusions according to the electric motors' classes commercially available.

Important industrial applications are based on magnetohydrodynamics (MHD), which concerns the flow of electrically conducting fluids immersed in external magnetic fields. Using the Finite Volume Method, we performed a 3D numerical study of the MHD flow of a conducting fluid in a circular duct. The flow considered was laminar and fully developed. Along the initial section of the duct, there were magnets placed around the duct producing magnetic fields in the radial direction. Two arrangements of magnetic field orientation were considered: fields pointing toward and away from the duct’s center alternately, and all fields pointing toward the duct’s center. For each arrangement of magnets, various intensities of magnetic fields were considered to evaluate two effects: the influence of the magnetic field on the flow velocity, and the influence of the flow velocity on magnetic field induction. It was found that for the second arrangement of magnets and Hartmann numbers larger than 10, the flow velocity was reduced by as much as 35%, and the axial magnetic induction was as high as the field intensity applied by each magnet. Those effects were negligible for the first arrangement and low fields because of the distribution of field lines inside the duct for these situations.

The main equipment responsible for connection and transmission of electric power from generating centers to consumers are power transformers. This type of equipment is subject to various types of faults that can affect its components, in some cases also compromising its operation and, consequently, the electric power supply. Thus, in this paper, electromagnetic, thermal, and structural analysis of power transformers was carried out with the objective of providing the operator with information on the ideal moment for performing predictive maintenance, avoiding unplanned shutdowns. For this, computational simulations were performed using the finite element method (FEM) and, from that, the different transformer operation ways, nominal currents, inrush current, and short-circuit current were analyzed. In this perspective, analyses of the effects that thermal expansion, axial forces, and radial forces exerted were carried out, contributing to possible defects in this type of equipment. As a study object, simulations were carried out on a 50 MVA single-phase transformer. It is important to emphasize that the simulations were validated with real data of measurements and with results presented in the current literature.

The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, greenhouse gas emissions and energy efficiency levels of lighting and air conditioning system, according to the mandatory technical regulation in public buildings in Brazil. Presenting a solution to assist in the decision making of engineers, architects or building managers for the optimal arrangements’ choice for lighting and air conditioning equipment, considering each built environment and project profile. For the validation process, a basic building was created with 15 rooms spread over three floors, according to the most common construction parameters in the North of Brazil. First, different combinations of objective-function candidates were investigated to compose the multi-objective algorithm fitness function, analyzing its performance in two central scenarios: (1) adding some “baits” in air conditioning equipment files, and (2) without this inclusion. Thus, it was found that considering only three objective functions—incremental cost, energy consumption and the air conditioning energy efficiency coefficient—it is possible to get optimal non-dominated solutions in both scenarios, thus highlighting the robustness of the proposed methodology.

Global energy systems are undergoing a transition process towards renewable energy and energy efficiency practices. Induction motors play an important role in this energy transformation process since they are widely used as industrial loads, representing more than 53% of global energy consumption. With more countries adopting minimum energy performance standards through more efficient induction motors, comparisons between these new technologies in the presence of electrical disturbances must be systematically evaluated before adopting a substitution policy in the industry. To this end, this work presents a comparative analysis of the impact of harmonic voltages on the performance and temperature rise of electric motors classes IE2, IE3 and IE4 in the same operational conditions in view of future substitutions. The results show that under ideal operating conditions the IE4 class permanent magnet motor has better performance in terms of consumption and temperature, however presenting non-linear characteristics. In the presence of voltage harmonics, this scenario changes completely according to the harmonic content. Finally, aiming to analyze the harmonics influence in the motor temperature rise a statistical analysis by means of Spearman correlation matrices is presented.

This paper presents a novel analysis methodology to detect degradation in electrical contacts, with the main goal of implanting a predictive maintenance procedure for sectionalizing switches, circuit breakers, and current transformers in bays of electric transmission and distribution substations. The main feature of the proposed methodology is that it will produce a predictive failure indication for the system under operation, based on the spectral analysis of the load current that is flowing through the bay’s components, using a defined relationship similar to the signal-to-noise ratio (SNR) used in data communication. A highlight of using the proposed methodology is that it is not necessary to make new investments in measurement devices, as the already-existing oscillography measurement infrastructure is enough. By implementing the diagnostic system proposed here, electrical utilities will have a modern tool for monitoring their electrical installations, supporting the implementation of new predictive maintenance functions typical of the current electrical smart grid scenario. Here, we present the preliminary results obtained by the application of the proposed technique using real data acquired from a 230 kV electrical substation, which indicate the effectiveness of the proposed diagnostic procedure.

Brazil has started an energy transition process through more efficient electric motors. The new legislation determining the IE3 Class as the minimum efficiency level in commercial electric motors became valid in August 2019. Currently, four induction motor classes are defined by the IEC 60034-30-1, with the IE4 class being the most efficient, and in the same way, proposals to achieve IE5 efficiency class are available in the market. Considering the upcoming new technologies, it is necessary to know the impact of power systems disturbances in IM's in view of future substitutions. This paper presents a detailed analysis of the impact of different percentages of under and over voltage unbalances on the temperature and performance of electric motors classes IE2, IE3 and IE4. Results show that the IE4 hybrid motor presents non-linear characteristics, being observed this motor shows less dependence on voltage variation, mainly undervoltage unbalance. An analysis of how this phenomenon impacts on the current harmonic distortions in the induction motors operation is also developed through Spearman's correlation matrices. Finally, models that represent the temperature increase of each motor with different voltage unbalance conditions are presented.

Direct lightning discharges in overhead distribution networks invariably cause serious insulation damage, frequently leading to the electric system’s partial or total shutdown. Installing lightning arresters can be very effective, and it is commonly used to minimize this problem; however, considering that typically, electric distribution grids exhibit a very large number of electrical nodes, the massive use of lightning arresters may not be economically viable. In this way, this article proposes a methodology for allocating lightning arresters that can significantly reduce the number of lightning arresters installed, but at the same time maintaining an adequate protection level for the distribution grid. The proposed methodology, named Direct Discharge Crossing (DDC), analyzes the network criticality based on two main factors, which are the overvoltage magnitudes and the number of flashovers provoked by lightning discharges, and defines a feeder lightning performance function that is used to indicate the recommended location for lightning arresters’ installation. The simulation studies are accomplished using the IEEE 34 bus distribution grid and ATP software to demonstrate the efficacy of the proposed solution, which is confirmed by the results presented.

The measurement and analysis of partial discharges (PD) are like medical examinations, such as Electrocardiogram (ECG), in which there are preestablished criteria. However, each patient will present his particularities that will not necessarily imply his condemnation. The consolidated method for PD processing has high qualifications in the statistical analysis of insulation status of electric generators. However, although the IEEE 1434 standard has well-established standards, it will not always be simple to classify signals obtained in the measurement of the hydro generator coupler due to variations in the same type of PD incidence that may occur as a result of the uniqueness of each machine subject to staff evaluation. In order to streamline the machine diagnostic process, a tool is suggested in this article that will provide this signal classification feature. These measurements will be established in groups that represent each known form of partial discharge established by the literature. It was combined with supervised and unsupervised techniques to create a hybrid method that identified the patterns and classified the measurement signals, with a high degree of precision. This paper proposes the use of data-mining techniques based on clustering to group the characteristic patterns of PD in hydro generators, defined in standards. Then, random forest decision trees were trained to classify cases from new measurements. A comparative analysis was performed among eight clustering algorithms and random forest for choosing which is the superior combination to make a better classification of the equipment diagnosis. R2 was used for assessing the data trend.

This article presents a comparison of using techniques of optimal load flow and decision tree in making corrective voltage control actions for electrical power systems under insecure operation condition, that is, with voltage constraints violated. The decision tree technique is used in conjunction with a technique of sensitivity analysis in such a way that control actions are taken to be more effective to eliminate the voltage constraints violation in each case of contingency analyzed. A comparison is made between the control actions suggested by the optimal load flow strategy and those suggested by the decision tree for the same operating condition, discussing the achievement of implementing these actions in a real power system. The analysis methodology proposed here is tested in a real power system of a Brazilian utility, which operates in the State of Amapá - Brazil. The results showed how both methodologies can be used as operational tools in power system supervision and control centers.

Assessing the transient behavior of electric power transmission/distribution systems, when they are subjected to major disturbances such as lightning discharges, is an essential procedure to ensure the operational security of these systems, in order to supply good quality power to all consumers. Electromagnetic transient studies are routinely performed in the planning and operation phases of these systems, by using world widely known computer programs, among which stands out the Alternative Transient Program (ATP), via its graphical interface ATPDraw. However, preparing files for running case studies by using ATPDraw can become a time-consuming and human error-prone task. To overcome this drawback, this paper presents a toolbox for automatic generation and execution of Alternative Transient Program input files based on information directly obtained from technical databases of distribution utilities. This toolbox aims to reduce modeling time and susceptibility to human errors in the process of describing the grid in the software input file, which constitute the biggest obstacles to the extensive use of this program in real electric transmission/distribution networks. For the toolbox validation, a comparison was made between the input file generated by the ATPDraw auxiliary graphic interface and the file generated by the proposed toolbox by using the IEEE 13-bus and IEEE 34-bus test feeders. Besides that, the simulation results of both feeders for both softwares were compared, so that the correct operation of the Alternative Transient Program automatic case creator and executor proposed in this article were proved. In addition, the automatic generation of ATP cases for larger grids is exemplified with the IEEE 123-bus test feeder.

Metodologias com abordagens diferenciadas que auxiliem o ensino e a aprendizagem em sala de aula têm sido muito estudadas, como a utilização da robótica educacional, laboratórios virtuais e dispositivos físicos que são ferramentas educacionais que atualmente estão se destacando quando se trata de novas propostas metodológicas para o ensino de Ciências e Matemática. Este trabalho investigou a utilização de um recurso para fins educativos por meio da plataforma BBC Micro:bit, como forma de engajar, motivar e promover o letramento computacional e científico dos estudantes dentro de uma cultura maker. A Aprendizagem Baseada em Projeto (PBL) e a interdisciplinaridade de forma integrada pelas disciplinas de Ciências, Tecnologias, Engenharia, Artes e Matemática (STEAM), por meio da metodologia STEAM, foram utilizadas nesta pesquisa. Foi elaborada uma oficina com o uso do Micro:bit, aplicada aos estudantes do primeiro ano do curso técnico em Informática, modalidade ensino médio regular da EETEPA Dr. Celso Malcher. Observou-se a partir dos resultados analisados o Micro:bit pode ser utilizado como ferramenta metodológica para ensinar os conteúdos vistos em sala de aula, principalmente quando utiliza-se a PBL e a metodologia STEAM de forma integrada.

The electrical insulation is one of the main sources of failures in hydro-generators, therefore it is important to research the insulation system of stator bars. In this paper, it is developed a steady-state multiphysics analysis of a stator bar using the Finite Element Method to assess its steady-state behavior in the electrical, magnetic and thermal domains. Different aspects are analyzed in simulations, such as capacitance, mechanical stress and thermal effects. Numerical results are compared with experimental measurements for validation.

Diante do período pandêmico gerado pelo COVID-19, um novo formato de ensino foi exigido simultaneamente à necessidade do distanciamento social, com o uso de tecnologias digitais. Estas, apesar de incentivadas na educação em períodos anteriores, ainda não tinham sido integradas significativamente no cotidiano escolar. O cenário da pandemia, no entanto, apontou para a necessidade da adoção dessas tecnologias, recomendada pelos documentos expedidos pelo MEC e CNE no período. Dessa forma, o objetivo desta pesquisa é relatar a partir de um podcast, as experiências e percepções de professores de Ciências atuando prioritariamente na Amazônia brasileira, ainda que professores de outros estados tenham sido convidados, quanto ao uso de recursos digitais em sala de aula, bem como divulgar projetos e produções educacionais voltadas para o ensino de Ciências. Para tanto, foram entrevistados onze profissionais da educação dos municípios: Rio Branco (AC), Xapuri (AC), Coari (AM), Oriximiná (PA), Santo Antônio do Tauá (PA), Belém (PA), Ponta de Pedras (PA), Barreiras (BA), Barra do Bugres (MT), Guarantã do Norte (MT) e Cabedelo (PB). As entrevistas foram gravadas e editadas em softwares livres e distribuídas em diversas plataformas de streaming desde o início de julho de 2020, tendo atualmente um total de 434 audições. Constatou-se que apesar das inúmeras dificuldades relatadas pelos docentes com o uso de tecnologias digitais, principalmente em tempos de pandemia, a incorporação das Tecnologias Digitais da Informação e Comunicação no ensino, bem como a utilização do podcast como instrumento de divulgação científica e democratização do acesso à informação.

Buildings' energy consumption has a great energetic and environmental impact worldwide. The architectural design has great potential to solve this problem because the building envelope exerts influence on the overall system performance, but this is a task that involves many objectives and constraints. In the last two decades, optimization studies applied to energy efficiency of buildings have helped specialists to choose the best design options. However, there is still a lack of optimization approaches applied to the design stage, which is the most influential stage for building energy efficiency over its entire life cycle. Therefore, this article presents a multi-objective optimization model to assist designers in the schematic building design, by means of the Pareto archived evolutionary strategies (PAES) algorithm with the EnergyPlus simulator coupled to evaluate the solutions. The search process is executed by a binary array where the array components evolve over the generations, together with the other building components. The methodology aims to find optimal solutions (OSs) with the lowest constructive cost associated with greater energy efficiency. In the case study, it was possible to simulate the process of using the optimization model and analyze the results in relation to: a standard building; energy consumption classification levels; passive design guidelines; usability and accuracy, proving that the tool serves as support in building design. The OSs reached an average of 50% energy savings over typical consumption, 50% reduction in CO2 operating emissions, and investment return less than 3 years in the four different weathers.

Currently, for analyzing harmonic impacts on voltage at a point of interest, due to multiple nonlinear loads, the literature recommends carrying out simultaneous and synchronized measurement campaigns in all suspicious points with the use of high cost energy quality analyzers that are usually not available at the customers’ facilities and very often also not at the electric utilities. To overcome this drawback this paper proposes a method of assessing the harmonic impact due to multiple nonlinear loads on the total voltage harmonic distortion using only the load current true RMS values which are already available in all customers’ installations. The proposed methodology is based on Regression Tree technique using the Permutation Importance indicator which is validated in two case studies using two different electrical systems. The first case study is to ratify the use of Permutation Importance to measure the impact factor of each nonlinear load in a controlled scenario, the IEEE-13 bus test system, using ATP simulation (Alternative Transient Program). The second is to apply the methodology to a real system, an Advanced Measurement Infrastructure System (AMI) implanted on a campus of a Brazilian University, using low cost meters with only true RMS current measurements. The results achieved demonstrated the feasibility of applying the proposed methodology in real electric systems without the need for additional investments in high-cost energy quality analyzers.

This paper proposes the development of a three-phase state estimation algorithm, which ensures complete observability for the electric network and a low investment cost for application in typical electric power distribution systems, which usually exhibit low levels of supervision facilities and measurement redundancy. Using the customers´ energy bills to calculate average demands, a three-phase load flow algorithm is run to generate pseudo-measurements of voltage magnitudes, active and reactive power injections, as well as current injections which are used to ensure the electrical network is full-observable, even with measurements available at only one point, the substation-feeder coupling point. The estimation process begins with a load flow solution for the customers´ average demand and uses an adjustment mechanism to track the real-time operating state to calculate the pseudo-measurements successively. Besides estimating the real-time operation state the proposed methodology also generates nontechnical losses estimation for each operation state. The effectiveness of the state estimation procedure is demonstrated by simulation results obtained for the IEEE 13-bus test network and for a real urban feeder.

Computer Numerical Control (CNC) is a technology made up of several blocks. Among these, lies the Trajectory Planning block, responsible for reference profile generation that are fed to position control loops. The need for Trajectory Planning arises from the mechanical constraints inherent to every plant to which CNC technology is applied. The machine's operational limits myst be respected, in order to avoid several issues, such as: loss of precision, early wear of machine's parts and excessive vibration. This paper proposes a novel smooth real-time trajectory generation setup based on an embedded system platform. A real-time snap and jerk bounded control algorithm is proposed, to achieve continuous and smooth feed motion in traditional Numeric Control code file, dealing both with straight lines and arcs. A local motion blending algorithm, applicable to the proposed method, is also presented. The developed algorithm was deployed to a BeagleBone Black, an embedded System-on-Chip, single board computer and tested in a prototype router machine. A comparison between the proposed method against the seven segments and trapezoidal acceleration methods is presented, both in terms of performance and of real-time computing viability. Simulation and Experimental results demonstrate the effectiveness of the proposed method to generate velocity, acceleration, jerk and snap bounded three dimensional trajectories, reducing the RMS error in up to 8.2% and 22.38% when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively. Assessing the error area on straight angles, the proposed method produced error areas 24% and 80% smaller when compared to the Seven Segments and to Trapezoidal Acceleration methods, respectively.

The efficient protection of electric power distribution networks against lightning discharges is a crucial problem for distribution electric utilities. To solve this problem, the great challenge is to find a solution for the installation of surge arresters at specific points in the electrical grid and in a sufficient quantity that can ensure an adequate level of equipment protection and be within the utility’s budget. As a solution to this problem of using ATP (Alternative Transient Program), this paper presents a methodology for optimized surge arrester allocation based on genetic algorithm (GA), with a fitness function that maximizes the number of protected equipment according to the financial availability for investment in surge arresters. As ATP may demand too much processing time when running large distribution grids, an innovative procedure is implemented to obtain an overvoltage severity description of the grid and select only the most critical electric nodes for the incidence of lightning discharges, in the GA allocation procedure. The results obtained for the IEEE-123 bus electric feeder indicate a great reduction of flashover occurrence, thus increasing the equipment protection level.

O presente artigo vem demonstrar a importância da Robótica Pedagógica como forma de ensino nos anos finais do Ensino Fundamental, por meio do resgate do Programa Um Computador por Aluno (Prouca) para a Robótica Pedagógica, as plataformas Arduino e Ardublockly, de acordo com a BNCC – Base Nacional Comum Curricular junto ao Ensino de Ciências – Física. Com isso, desenvolveu-se uma análise quantitativa, a partir de projeto de oficinas e treinamentos de introdução à robótica pedagógica na escola municipal Major Cornélio Peixoto no município de Santo Antônio do Tauá no estado do Pará, possibilitando aos professores e alunos a oportunidade de ampliar as discussões das teorias estudadas em sala de aula, com apoio do Laboratório de Engenhocas da Universidade Federal do Pará (UFPA). observou-se, que a utilização da Robótica Pedagógica deve ser incentivada, planejada e desenvolvida considerando os aspectos de aprendizagem, interagindo de forma consciente com os alunos, propiciando um despertar ativo e dedicado, o que irá refletir positivamente no desenvolvimento crítico do aluno com relação aos seus conhecimentos científicos, estimulando para a formação de futuros engenheiros, e profissionais da área de Ciências Exatas em geral, para que possam utilizar de todo aprendizado adquirido na área de ciência e tecnologia, para assim, ingressarem de forma qualificada no mercado de trabalho.

Sympathetic inrush current phenomenon occurs when a transformer is switched on in a power network containing other transformers that are already energized. This interaction significantly changes duration and magnitude of transient magnetizing currents in the transformers involved and may lead to misoperation of these equipment. Therefore, in this paper it is presented the results of electromagnetic analysis due to sympathetic inrush and inrush current phenomenon among single-phase 50 MVA transformers in a power substation in the northern region of Brazil. For this purpose, the nine single-phase transformers installed at SE Guamá forming three three-phase banks, were modeled in the ATP software to obtain the energization behavior. In this paper the electromagnetic analyzes are performed in steady state, so only the first peak is used. In this way, results of the electromagnetic behavior of transformers are presented and compared sympathetic inrush with inrush current.

Um dos fatores que impulsionaram o desenvolvimento de diversas tecnologias é a busca constante da humanidade pelo conforto e comodidade. Isso está diretamente relacionado ao desenvolvimento da automação residencial. No entanto, devido à complexidade e custos elevados estes sistemas são privilégios apenas de alguns indivíduos. Em vista disso, este trabalho apresenta uma análise comparativa entre três projetos para a automação do sistema de iluminação de uma residência. Dois dos sistemas de automação foram desenvolvidos pelos próprios autores para uma implantação de baixo custo utilizando microcontroladores (Arduino e ESP32) através de diferentes canais de comunicação sem fio (Wi-Fi e Bluetooth), o terceiro sistema é um dispositivo que já existe no mercado. Esses sistemas de automação foram implementados em um modelo de residência popular e comparados entre si em termos de consumo de energia, custo de implementação e eficiência de projeto. Os três sistemas foram analisados com dois tipos diferentes de lâmpadas para resultados mais consistentes. Onde um dos objetivos deste trabalho é mostras que é possível incorporar parâmetros de automação residencial de baixo custo em casas populares.

With the increasing use of nonlinear loads in homes in Brazil comes the problem of harmonic injection in the power system and increasingly is a problem for the electric sector that needs to scale it. Knowing the loads that consume energy and inject harmonics into the system is important so that solutions are sought to make the use of the system more efficient and improve the quality of the energy that circulates in the electrical grid. This work presents simulations of DHTv and DHTi of a set of residences in order to predict the behaviour of the load over time, using previous measurements. The modelling is conducted using an ANFIS, which uses a neural network to adjust the parameters of the output that uses fuzzy rule to determine the output values of the system.

Atualmente, são utilizados diversos processos para a geração de energia elétrica, como por exemplo: usinas hidrelétricas, termoelétricas, nucleares, eólicas, solares, entre outras. Também, neste atual cenário, podem-se ressaltar as usinas virtuais, pois estas são responsáveis por disponibilizar energia por meio de ações de eficiência energética. Portanto, este artigo apresenta o direcionamento a esta forma de geração de energia, a qual fica disponibilizada, por alguma ação de eficiência energética, para outro uso na sociedade. A usina virtual apresentada neste trabalho é baseada em pesquisas de ações de eficiências no sistema nacional de iluminação pública por meio do uso de lâmpadas com maior índice de eficiência e maior vida útil, o que permite a disponibilidade de energia a outros setores, reduzindo gastos quanto a investimentos e melhorando os níveis de tensões do sistema elétrico. Com isso, pode-se considerar como uma usina geradora de energia.

This paper presents a procedure to estimate the impacts on voltage harmonic distortion at a point of interest due to multiple nonlinear loads in the electrical network. Despite artificial neural networks (ANN) being a widely used technique for the solution of a large amount and variety of issues in electric power systems, including harmonics modeling, its utilization to establish relationships among the harmonic voltage at a point of interest in the electric grid and the corresponding harmonic currents generated by nonlinear loads was not found in the literature, thus this innovative procedure is considered in this article. A simultaneous measurement campaign must be carried out in all nonlinear loads and at the point of interest for data acquisition to train and test the ANN model. A sensitivity analysis is proposed to establish the percent contribution of load currents on the observed voltage distortion, which constitutes an original definition presented in this paper. Initially, alternative transient program (ATP) simulations are used to calculate harmonic voltages at points of interest in an industrial test system due to nonlinear loads whose harmonic currents are known. The resulting impacts on voltage harmonic distortions obtained by the ATP simulations are taken as reference values to compare with those obtained by using the proposed procedure based on ANN. By comparing ATP results with those obtained by the ANN model, it is observed that the proposed methodology is able to classify correctly the impact degree of nonlinear load currents on voltage harmonic distortions at points of interest, as proposed in this paper.

This study presents an approach to calculate average technical losses (TLoss) and non-technical losses (NTLoss) in distribution grids using an equivalent operational impedance (EOI) calculated from a load flow solution for the transformers’ average loads, obtained from customers’ electric bills. If transformers are supervised, i.e. have available active and reactive power injections measurements or estimates from a state estimator program, the transformers’ average technical and non-technical losses can be calculated by running a load flow for the grid supplied by the transformer and using the definition of EOI presented in this study. For unsupervised transformers, i.e. no measurements or estimates are available, pseudo measurements of average active and reactive power injections can be obtained by a procedure that uses active and reactive power measurements at the feeder substation. The use of this methodology by electric utilities allows the calculation of technical and non-technical losses more accurately, as well as the inclusion of non-technical losses in the distribution networks operation planning. Results using the IEEE 13-bus test system and an urban real distribution grid are presented to demonstrate the effectiveness of the proposed methodology

The objective of this paper is to investigate the behavior of electromagnetic forces during the occurrence of faults inside transformers as result of transients in the electrical systems. The methodology is based on the modeling of a single-phase 50-MVA transformer subjected to inrush currents through finite-element method. In this perspective, the values of inrush currents, obtained by the alternative transient program software, are used to estimate the magnetic field density dispersion in the transformer, and to find the values of forces in axial and radial directions. These forces components are distributed along the energized windings for observing the loads behavior in high-voltage windings. This paper will thus present investigations of electromagnetic forces, structural deformation, stresses, and safety factor on transformer's winding when subjected to inrush current.

This paper presents a new method for load pre-dispatch considering the technical conditions of engines in thermoelectric power plants by combining several maintenance and diagnostic techniques and using computational intelligence. A diagnosis of the technical conditions of the engines is performed using a lubricant analysis, vibration analysis, and thermography. With these data from a statistical analysis, it is possible to predict when an engine will fail and to consider this phenomenon in the load pre-dispatch. To increase the engine reliability and power supply, a maintenance management program is developed using MANAGEMENT tools, applying only 4 total productive maintenance pillars and combining them with predictive maintenance and diagnostics, thus reducing failures in plant equipment. Some results achieved after this implementation are as follows: a reduction in the annual cost of maintenance, a reduction in the corrective maintenance, an increase in the mean time between failures, and a decrease in the mean time to repair in all areas. In addition, the pre-dispatch ensures that the demanded power is met with a high degree of reliability and quality, and at minimal cost.

Economic-emission load dispatch optimization problem is an essential task in power plants with internal combustion engines. In power plants, in addition to electricity, a lot of air pollution by exhaust gases is generated. There are many international standards that establish the permissible limits of different substances but still have not developed an expression to evaluate the environmental impact caused by all components of the exhaust gases as a whole. A new method to evaluate this impact is developed in this paper. The developed mathematical expression was called “emission index.” To get a better idea of the environmental impact of each type of engine, the “specific emission index”, which is the emission index divided by the power delivered by the engine. This paper also presents a mathematical model for a multiobjective optimization of economic-emission load dispatch using nondominated sorting genetic algorithm II.

The development of a preventive control methodology to increase the capacity of voltage sag recovery (Fault Ride Through Capability (FRTC)) of a doubly-fed induction generator (DFIG) connected in an electrical network is presented. This methodology, which is based on the decision trees (DT) technique, assists with monitoring and support for security and preventive control, ensuring that wind systems remain connected to the power system even after the occurrence of disturbances in the electric system. Based on offline studies, DT discovers inherent attributes of the FRTC scenario related to electrical system behavior and provides a quick prediction model for real-time applications. From the obtained results, it is possible to check that the DFIG is contributing to a system’s operation security from the availability of power dispatch and participation in the voltage control. It is also noted that the use of DT, in addition to classifying the system’s operational state with good accuracy, also significantly facilitates the operator´s task, by directing him to monitor the most critical variables of the monitored operation state for a given system’s topological configuration.

The objective of this paper is to investigate the behavior of electromagnetic forces during the occurrence of faults inside transformers as result of transients in the electrical systems. The methodology is based on the modeling of a single-phase 50-MVA transformer subjected to inrush currents through finite-element method. In this perspective, the values of inrush currents, obtained by the alternative transient program software, are used to estimate the magnetic field density dispersion in the transformer, and to find the values of forces in axial and radial directions. These forces components are distributed along the energized windings for observing the loads behavior in high-voltage windings. This paper will thus present investigations of electromagnetic forces, structural deformation, stresses, and safety factor on transformer's winding when subjected to inrush current.

O presente artigo tem como objetivo apresentar um relato de experiência que pretende investigar a robótica pedagógica, como ferramenta auxiliadora na disciplina de ciência, que vem sendo desenvolvida em uma escola de ensino fundamental na cidade de Santo Antônio do Tauá – Pará. Tema finalidade de investigar a contribuição da robótica pedagógica nas aulas de ciência com o uso de kit educacional Arduino. Foi desenvolvida pesquisa de caráter observacional, que constatou a robótica como um instrumento fundamental na contribuição do desenvolvimento do aluno de maneira eficiente, explorando habilidades como o raciocínio, cooperação, a inovação criativa, a ludicidade e a interdisciplinaridade, elementos substanciais na escola atual. Além disso, estabeleceu-se relação entre as atividades da robótica pedagógica com os pressupostos do lúdico na educação, visto que os robôs propostos se tornam brinquedos durante as atividades. Isto evidencia a necessidade de incentivar o estudo criativo-científico da robótica enquanto atividade pedagógica significativa nas aulas de ciências. Com isso, desenvolveu-se uma análise sobre a importância da Robótica Pedagógica enquanto recurso didático nas aulas de ciências em correlação com lúdico em sala de aula, utilizando a plataforma Arduino (experiências) e o Ardublockly (programação) como instrumentos materiais. Os pilares desta pesquisa estão fundamentados em Seymour Papert com a teoria do construcionismo, idealizador e disseminador da robótica pedagógica no ambiente escolar, buscando a construção do conhecimento de maneira interdisciplinar.

In this paper, a methodology was developed to analyze the results of energy efficiency programs used in the electricity distribution sector in Brazil. Analyzing the gains obtained through the investments made, and classifying which actions resulted in the best performance, contributed to decision making on the best allocation of investments to obtain the greatest energy savings. The Brazilian Energy Efficiency program was analyzed with a developed non-parametric model, using the data envelopment analysis method, and the categories of projects with better performance were determined. A database of the results from 1704 projects, from 2008 to 2016 in the Energy Efficiency program in Brazil´s electricity distribution sector, was used. The results obtained show that the best performance was achieved by projects in the industrial and cogeneration categories; however, in Brazil these constitute only 4.24% of the projects presented and 5.28% of the total investments in the last eight years, indicating a need to review the regulatory strategies for energy efficiency in this country.

This paper proposes a new methodology based on the use of Resonance Index (RI) analysis as a posteriori decision-making procedure to check solutions of the optimization algorithm NSGA-II against resonance, when applied to the capacitor banks placement problem in radial distribution systems. Most of existing methodologies approach harmonic resonance in the referred problem through the inclusion of constraints in the optimization procedure with respect to the harmonic distortion indexes THD and IHD. However, monitoring only these two parameters is not sufficient to identify specific problems on capacitor banks due to harmonic resonance. To demonstrate this point, a RI analysis using the resonant chart was performed considering a 34-bus radial system. Also, the proposed a posteriori analysis is compared with the one that includes directly RI as a constraint in the optimization procedure, demonstrating that the proposed approach has a better performance with respect to computational time.

This study investigates the effects on the performance of a diesel generator set at constant electric power of 2.43 kW (approximately 60% nominal engine load condition) and rotation at 3600 rpm operating with a 7% biodiesel-diesel blend (B7) and being doped with hydrogen into the intake air. Hydrogen was injected continuously into the engine intake manifold at different mass concentrations of 2, 6, 8 and 10% of the total fuel mass (B7 + hydrogen) which represents energy fractions of 5, 15, 20 and 24% of total fuel energy. To this, a small L-shaped tube installed at the center of the pipe was used. It is anticipated that the intake air fluctuations at that location, due to opening and closing the intake valve, allows a rapid mixture of hydrogen and air. Due to the addition of hydrogen the total amount of energy in the fuel (B7 + hydrogen) introduced into the engine was increased, so that the engine speed tends to increase, but this was prevented by the governor of the fuel injection pump which decreases the amount of B7 injected until the working frequency of the generator was 60 Hz. The test results showed a reduction in the specific fuel consumption as a function of the increase of hydrogen concentrations. Likewise, CO2, CO and HC emissions decreased proportionately as the hydrogen concentration was increased. On the other hand, the emissions of nitrogen oxides (NOx) increased due to the increase in the average temperature inside the cylinder. There was also an increase in the peak pressure and in the heat release rate inside the cylinder, since B7 ignition delay was reduced due to the increase in hydrogen content.

Industrial production has evolved significantly over the last decade. For this reason, it is necessary to obtain mathematical and computational tools that enable power systems engineers to make decisions that reduce harmonic distortions in accordance with international standards. This paper presents a total harmonic distortion (THD) assessment based on full knowledge discovery in databases (KDD) using power quality (PQ) standards and computational intelligence tools. The materials and methods of THD assessment consist of load and layout analysis; choice and installation of PQ analyzers; and the application of the full KDD process, including collection, selection, cleaning, integration, transformation and reduction, mining, interpretation, and evaluation of the data. This research methodology was used in an electrical and electronic industry; the results obtained have characteristics that can be used as a reference for other types of analyses. The results indicate that these methods can be applied to several industrial applications such as: 1) the description of the complete KDD process for THD assessment of the point of common coupling; 2) simultaneous collection using five PQ analyzers at several points in the electrical network; and (3) the use of a decision tree classifier.

This paper presents a specific method to improve the reliability of the equipment and the quality of power supplied to the electrical systems with the frequency and voltage control of a thermoelectric plant, to guarantee a more stable system. The method has the novelty of combining Total Productive Maintenance (TPM) using only four pillars, with Electrical Predictive Maintenance based in failure analysis and diagnostic. It prevents voltage drops caused by excessive reactive consumption, thus guaranteeing the company a perfect functioning of its equipment and providing a longer life of them. The Maintenance Management Program (MMP) seeks to prevent failures from causing the equipment to be shut down from the electrical system, which means large financial losses, either by reducing billing or by paying fines to the regulatory agency, in addition to prejudice the reliability of the system. Using management tools, but applying only four TPM pillars, it was possible to achieve innovation in power plants with internal combustion engines. This study aims to provide maintenance with a more reliable process, through the implantation of measurement, control and diagnostic devices, thus allowing the management to reduce breakdown of plant equipment. Some results have been achieved after the implementation, such as reduction of annual maintenance cost, reduction of corrective maintenance, increase of MTBF (Mean Time between Failures) and reduction of MTTR (Mean Time to Repair) in all areas. Probabilistic models able to describe real processes in a more realistic way, and facilitate the optimization at maximum reliability or minimum costs are presented. Such results are reflected in more reliable and continual power generation.

This paper proposes a methodology for compression of electrical power signals from waveform records in electric systems, using genetic algorithm (GA) and artificial neural network (ANN). The genetic algorithm is used to select and preserve the points that better characterize the waveform contours; and the artificial neural network is used in the compression of other points as well as on the signal reconstruction process. Thus, the data resulting from the proposed methodology are formed by a part of the original signal and by a compressed complementary part in the form of synaptic weights. The proposed methodology selects and preserves a percentage of the original signal samples, which are aspects not explored in the literature. The method was tested using field data obtained from an oscillographic recorder installed in a 230 kV electrical power system. The results presented compression rates ranging from 8.59:1.00 to 24.16:1.00 for preservation rates ranging from 2.5% to 10%, respectively.

This work presents a hybrid method to solve the protective devices allocation problem in electric distribution systems. Current methods only consider optimization results, without taking into account standards established by electric energy companies. These standards reflect distribution systems particularities observed by these companies. Firstly, recloser placementis determined through an optimization process, aiming to reduce reliability indices. Fuse links are placed according to heuristic rules established by electric companies. To validate the proposed methodology, a comparison with three other references from the literature is carried out, showing good results and proving the method's effectiveness.

The search for effective ways to promote the secure operation of power systems and to increase its understanding by operators has encouraged continuous research for new techniques and methods that can help in this task. In this paper, it is proposed an approach to assess power system operation security for multiple contingencies using a multiway decision tree (MDT). The MDT differs from other decision tree techniques for establishing, in the training step, one value of the categorical attributes by branch. This approach proposes the use of topologies (contingencies) as categorical attributes. In this way, it improves interpretability regarding the power system operational state, as the operator can see clearly the critical variables for each topology, such that the MDT rules can be used in aiding the decision-making. This proposal was used for security assessment of the Northern part of the Brazilian Interconnected Power System (BIPS), and it was tested with real data from one day operation, demonstrating good performance, with a set of simple and clear rules. It was also performed a comparison of the obtained results with other techniques based on DT and it turned out that MDT has resulted in a simpler procedure for power system security classification with good accuracy.

Partial discharge (PD) monitoring is widely used in rotating machines to evaluate the condition of stator winding insulation, but its practice on a large scale requires the development of intelligent systems that automatically process these measurement data. In this paper, it is proposed a methodology of automatic PD classification in hydro-generator stator windings using neural networks. The database is formed from online PD measurements in hydro-generators in a real setting. Noise filtering techniques are applied to these data. Then, based on the concept of image projection, novel features are extracted from the filtered samples. These features are used as inputs for training several neural networks. The best performance network, obtained using statistical procedures, presents a recognition rate of 98%.

A etiquetagem e as certificações ambientais em edificações tem se tornado uma realidade cada vez mais presente em vários países. No Brasil não é diferente, as construções eficientes são peças chave para a redução efetiva do consumo energético do país. O Programa Brasileiro de Etiquetagem de edificações (PBEedifica) possui equacionamento e software próprio para simulação da eficiência energética, porém a aplicação deste método ainda é feito apenas por um laboratório, responsável por atender a demanda de todo país. Faz-se necessário a busca de alternativas que estejam mais próximas da indústria de projeto, para que o profissional saiba o nível de eficiência alcançado, aplicando estratégias corretivas durante o processo criativo. A tecnologia BIM é altamente cotada para isso, por trabalhar com parâmetros simuláveis e propor a integração multidisciplinar. Neste trabalho realizou-se um estudo de caso do projeto arquitetônico e complementares de uma residência, localizada em Belém-PA, utilizando o conjunto de ferramentas BIM em todo o processo de concepção, identificando o grau de compatibilidade e contribuição que esta tecnologia pode trazer para projetos sustentáveis e etiquetagem do Procel, analisando o método mais viável para a utilização do mercado nacional e objetivando a disseminação da etiquetagem por parte dos projetistas.

Este artigo apresenta a análise de eficiência energética predial feita no edifício do Ceamazon, laboratório de pesquisas vinculado à Universidade Federal do Pará. Para este estudo foi utilizada a metodologia prescritiva do Regulamento Técnico da Qualidade para o Nível de Eficiência Energética de Edificações Comerciais, de Serviços e Públicas – RTQ-C. A análise foi feita principalmente nos sistemas de iluminação artificial e condicionamento de ar, visto que uma análise prévia dos dados de envoltória do prédio já havia coletado bons resultados. Serão apresentados também propostas de inclusão de alternativas energéticas para o edifício, visando uma eficiência energética ainda maior.

A natureza finita e a instabilidade no preço dos combustíveis fósseis atreladas à preocupação com a preservação do meio ambiente levaram a eficienciatização do uso da energia a ser um tópico de extrema importância no mundo atual em todas as áreas, não diferindo no setor naval. A IMO (International Maritime Organization), a responsável por instituir um sistema de colaboração entre governos no que se refere a questões técnicas que interessam à navegação comercial internacional, tem dedicado esforços significativos a fim de promover e regular a eficiência energética em navios nos últimos anos, diminuindo, assim, a emissão de gases do efeito estufa. A IMO desenvolveu, então, algumas medidas técnicas e operacionais como o Indicador Operacional de Eficiência Energética (EEIO), o Plano de Gestão de Eficiência Energética (SEEMP) e o Índice de Design de Eficiência Energética (EEDI), sendo os dois primeiros de caráter voluntário e o último obrigatório desde 01 de Janeiro de 2013 e assim justificando o estudo da eficientização do uso da energia nessa área. Este artigo mostra uma análise em eficiência energética direcionada à iluminação do navio patrulha Guarujá P49 com a proposta da troca das lâmpadas presentes no navio, incandescentes, halógenas e fluorescentes, por lâmpadas mais eficientes, as lâmpadas de LED, fazendo um estudo econômico e ambiental do consumo de combustível fóssil no caso atual e do caso proposto com o auxílio do software RETScreen.

Este artigo propõe as dimensões de um navio de passageiros confeccionado em alumínio para atender a um trecho da região metropolitana de Belém do Pará, mostrando ainda um comparativo com as h-lines de ônibus que atendem a área escolhida, relacionando preço, distância percorrida, tempo e conforto para os passageiros; e uma análise das emissões anuais de gases poluentes à atmosfera para ambos os casos através do software RETScreen. As localidades estabelecidas como únicas paradas foram o distrito de Icoaraci e a ilha de Outeiro, partindo da maior feira a céu aberto da América Latina, o Ver-o-Peso. De acordo com o último censo do Instituto Brasileiro de Geografia e Estatística (IBGE), Icoaraci conta com uma população de 167.035 habitantes, além de ser uma importante região turística através da exposição de cerâmicas indígenas, com sua orla banhada pela baía do Guajará e seu polo gastronômico composto principalmente pela culinária paraense. Outeiro, por sua vez, com cerca de 80 mil habitantes, é um dos destinos mais populares entre os veranistas que moram na capital do Pará, sendo bastante procurado não somente aos finais de semana de férias, mas durante o ano todo, justificando a importância de ambas as paradas atendidas pelo navio proposto. Este artigo tem como objetivo fazer um estudo comparativo entre os transportes públicos dos tipos hidroviário e rodoviário em distâncias relativamente pequenas, analisando aspectos econômicos, sociais e ambientais a fim de mostrar o potencial hidroviário da região Amazônica.

This study addresses the problem of determining which non-linear loads can be considered potential harmonic sources to the voltage harmonic distortions observed in the utility grid voltages. Statistical regression models are used to establish correlations between the simultaneously measured harmonic voltages, in the grid, and harmonic currents, at each non-linear individual load. First, the R-squared statistic is used to decide the goodness of fit of the developed models, giving indication on the relevance of the model. In order to overcome the limitation of the linear regression model based on voltage and current magnitudes measurements only, that imposes a constant behaviour for the background harmonic sources, a non-parametric regression model is suggested and a comparison between the performances of the two models is carried out. Field data from two real electrical systems, one having a 138 kV substation in which a large industrial load and a 34.5 kV rural long feeder are connected; and the other having four urban 13.8 kV feeders supplying industrial and commercial loads, were used to develop and validate the statistical models used in the application.

The formulations employed to the optimization of passive filters can be classified as formulations of a single objective or formulations with multiple objectives. The single-objective formulations normally are devoted to determine the filters of lowest cost that assure the compliance with the power quality standards, while in the multi-objective approaches are added other goals that are related with the improvement of the power quality indexes. In the presented approach, the problem of the reactive power compensation and the problem of the harmonic distortion compensation are considered a unified multi-objective problem in which is determined a set of passive filters that allows the obtaining of the maximum economic benefits as well as the maximum improvement of the power quality of the circuit. While several previous contributions solve the multi-objective problem by minimizing a single function composed of several sub-objectives, this work employs the non-dominated sorting genetic algorithm (NSGA-II) for the optimization of three independent objective functions. This algorithm obtains the Pareto front of the problem and allows the selection of the most effective solutions. The optimization method that presented in this work allows the selection by the algorithm of the filter type proper for compensation in a node of the circuit as well as the obtaining of their parameters. The set of possible filter configurations to place in one candidate node is defined by the user before the optimization is done. This is a distinctive characteristic of the presented approach that is tested with a practical example.

A tarifa branca, direcionada a consumidores de baixa tensão, visa promover uma mudança de hábitos, deslocando o consumo do período de pico para o fora de ponta. Como a adesão é opcional, sua implementação deve oferecer benefícios. Uma comparação entre as tarifas branca e convencional aplicadas a um mesmo perfil de consumo residencial, apresentada neste artigo, mostra a economia para o consumidor representada pela tarifa branca.

This paper proposes a decision tree (DT)-based security dispatch method applied to integrated electric power and natural-gas networks (IPGNs) against credible contingencies that may cause violations. Preventive adjustments to the optimal electric energy generation and gas production are carried out based on the security regions and boundaries of controllable variables determined by the DTs. The easily interpretable DT’s rules that describe the security regions are tractable constraints to be included in the optimization routines of electricity generation and gas production rescheduling. Some specific critical contingencies applied to the IEEE 118-bus test system integrated with the 15-node natural gas network are taken as examples to demonstrate a promising application of the proposed security dispatch method to restore IPGN security.

The main objective of this paper is to assist in the investigation of electromagnetic forces, structural deformation, stresses, and Safety factor when energizing unloaded transformers. The methodology is based on modeling of a single-phase 50 MVA transformer subjected to inrush currents through finite element method (FEM). In this perspective, the conditions of inrush currents are used to estimate the magnetic field density dispersion in the transformer and to find the values of forces in axial and radial directions. These components are distributed along the energized windings for observing the loads in high-voltage windings. Thus, this article will contributes with the investigations of a structural Analysis on transformers when subjected to inrush current.

Pesquisas desenvolvidas mostram que o Brasil possui um déficit de engenheiros. Esse cenário revela um obstáculo no sistema educacional, com reflexos na produção e inovação no mercado. Este fato dá-se devido à redução da procura por esta profissão. O desinteresse, segundo especialistas, está ligado à visão que os alunos do ensino médio têm em relação às disciplinas da área de exatas. Considerando a relevância desse tema os discentes da Universidade Federal do Pará Campus - Tucuruí através do Grupo de Pesquisa de Sistemas Elétricos e Mecânicos utilizando a metodologia PBL, juntamente com a plataforma de prototipagem Arduino e seus conhecimentos em áreas multidisciplinares da Engenharia tem o objetivo de propor oficinas para alunos do ensino médio como um incentivo a engenharia através do contato com o lado pratico das ciências exatas. Por tanto o presente trabalho apresenta a metodologia utilizada nas oficinas e os resultados das etapas realizadas.

A diesel generator was simulated operating with palm oil as fuel and hydrogen doping the inlet air. The objective was to investigate how the addition of hydrogen can accelerate the end of vegetable oil combustion, and consequently improve the electrical efficiency of the generator set up, for the same mass flow rate of fuel. The simulations were performed using AVL BOOST software and validated with experimental data. The generator was simulated operating with 75%, 80% and 100% of the nominal load using palm oil in nature, and hydrogen being injected at the intake manifold in parcels of 5% to a maximum of 20% in energy content by replacing the main fuel. The simulations showed increase in electrical power, reduction in specific fuel consumption, improving the overall efficiency of the generator set with 100% load. Good results were obtained with operation at 75% of the nominal load.

In the search for strategies to mitigate climate change, the promotion of renewable energy is a major challenge worldwide, particularly for developing countries such as Brazil and Colombia, which aim to diversify their power grids by using unconventional renewable energy sources. One of the main obstacles is the development of innovative projects. Increasing oil palm cultivation in the Amazon region for the food and biodiesel industries is producing a large volume of biomass. The present study outlines a methodology for analysis of renewable energy projects based on identification of environmental, economic, and social sustainability criteria and indicators (C&I) for the oil palm production chain. This methodology was then used to develop a computer simulation model in the RETScreen® International software environment for financial viability and risk analysis.

This paper proposes an analytical methodology to allocate and size active power photovoltaic generation (PVG) units with embedded DC/AC inverter (PVGI) to be integrated as concentrated or dispersed generation in isolated medium voltage electrical grids. The methodology considers multiple objectives: improving the electrical grid voltage profile; reducing active power losses and the diesel generation participation. To validate the proposed methodology, the IEEE 33 and 69 buses networks and an isolated real electrical system were simulated. The results obtained demonstrated that the proposed methodology is effective in providing a solution with improvement in voltage profile, active power losses reduction, diesel generation participation reduction.

Several authors have treated the optimization of passive filters in electric distribution systems. Optimization methods like: sequential quadratic programming (SQP), simulated annealing (SA), differential evolution (DE), artificial neural networks (ANN), particle swarm optimization (PSO), genetic algorithm (GA), etc., have been employed for optimizing certain configurations of passive filters. These optimization methods have been employed to solve several formulations of the problem of the project of filters. These formulations can be classified in: formulations of one or several objectives. The objective of the present work is to show the evolution of the formulation of this problem in the lasts years respect to the objective functions and constraints used. This analysis shows how the formulations employed have been upgraded from single-objective to multi-objective formulations to achieve a better representation of this complex problem.

Different methods of optimization have been used for the selection and localization of capacitor banks in distribution circuits. However, it is necessary to consider the distortion taken place by the harmonics of the no-linear loads and the possible appearance of resonances between the inductive elements of the system and the existent capacitor banks. On the other hand, it has not been integrated in a single methodology the use of capacitor banks and of passive harmonic filters to compensate the reactive power in harmonic polluted distribution systems. The present work intends as objective to develop this methodology. The developed program is based on the multi-objective optimization algorithm NSGA-II that it is proven with success in several examples.

Este artigo apresenta uma proposta de análise da qualidade de energia elétrica através do indicador THD (total de distorção harmônica) e do Fator de Potência em sistema trifásico de baixa tensão utilizando um sistema de inferência Fuzzy, tendo como resultado uma nova proposta para avaliação da qualidade de energia.

The Brazilian electrical utility companies must meet continuity indicators for energy supply, which are represented by the indices of average interruption duration and frequency, according to targets established by the Brazilian Regulatory Agency for Electrical Energy (ANEEL). In a nationwide base, ANEEL has defined 30 clusters, each one having specific targets for Customer Average Duration Interruption Index and Customer Average Frequency Interruption Index; still, very frequently the utility distribution companies are financially penalised for not meeting these indicator targets. This study proposes a decision support system based on machine learning techniques so that the utility distribution companies can emulate the characteristics and procedures used by the ANEEL, and help in obtaining more adequate customer groups to evaluate the duration and frequency indicators. The proposed system was applied in a case study of a distribution utility whose supply area is located in the Brazilian Amazonia. The methodology proved to be adequate for seeking better customer grouping configurations that could result in a decrease in goal violations as well as providing more consistent goals, considering the specific characteristics of each distribution utility. Although this methodology was applied to a Brazilian scenario it also can be applied to other distribution utilities worldwide.

This paper proposes a new approach to fault diagnosis in electrical power systems, which presents an aspect little explored in the literature that is the protective device failure detection together with the fault section estimation, since the majority of the methodologies so far proposed to fault diagnosis are limited to the fault section estimation alone. The proposed methodology makes use of operation states of protective devices as well as information related to the protection philosophy. Initially, these data undergo a preprocessing step to convert the format of 0 and 1 to percentage values. The conversion to percentage values allows the use of artificial neural networks, whose numbers of inputs do not depend on the number of alarms of the protection philosophy, or the type of bus arrangement or the number of circuit breakers. This allows the same set of neural networks to be trained and applied in different power systems with different protection schemes and bus arrangements. The proposed system has five neural networks, each containing few neurons and requiring 30 μ s to perform fault diagnosis. The proposed system was trained considering the IEEE 57-bus system, containing different selective protection schemes, and subsequently tested in the IEEE 14-bus, 30-bus, and 118-bus systems, and Eletronorte 230-kV real power system.

This paper presents a new methodology for identifying internal faults and inrush currents in power transformers based on the gradient of the differential current. The technique is to calculate the angle of the gradient vector along the curve of the differential current in the data window and through waveforms recognition techniques to identify the type of occurrence. The gradient vector of a function corresponds to a vector tangent to the curve at the point under consideration. The gradient vector, to move along the curve of the differential current, changes its angle to the horizontal reference. The behavior of the gradient vector angle, through statistical calculations will be used to identify the occurrence of internal faults or the presence of inrush currents. The method was tested by simulating various types of internal and external faults and also several cases of inrush currents in a power transformer which is modeled by the EMTP/ATP software and also by implementing the algorithm in MATLAB®®, presenting highly satisfactory results.

This paper presents a method to determine the individual harmonic influence of multiple harmonic-producing loads in an electrical power system. This method is based in the development of statistical models from measurement data using the polynomial-regression technique. A real case study is presented in order to show the performance of the proposed method.

The unbalanced electric networks analysis has upgraded from the sequence components frame models to the phase-coordinates frame models. The electric power distribution systems for industrial plants, commercial buildings or residential costumers can contain several network unbalances that can be easily represented by phase-coordinates models. The phase-coordinates models can be used for the analysis of distribution systems at fundamental frequency as well as for other frequencies and are well suited for the harmonic analysis of unbalanced networks. The formulation of the frequency scan method in a phase-coordinates frame, besides allowing for a more accurate modeling of unbalanced networks, allows the specification of harmonic injections of any type: single-phase or three-phase of the desired sequence. Therefore, it is possible to study the effect of the non-linear loads according to its features and connection to the circuit. This paper develops the phase-coordinates model of an unbalanced distribution power system, considering the representation of three-phase transformer banks of three or two single-phase transformers, as well as other asymmetries that can be found in the electrical systems of industrial plants, commercial or service facilities. The present model improves the representation of the single-phase transformer with mid-tap on the secondary side. The frequency scan based on the present model is tested with a simple example of a four-wire delta system that highlights the possibilities of the model in phase-coordinates.

The Computer Numeric Control (CNC) is a technology which aims to generate, parse and execute sequential actions that describes the behavior of the end effector. This article reports the development small sized prototype CNC machine, based on a modular system with the capability of communication through USB. It is also reported the development of the basic electronic devices to run a CNC machine and proposes, as well, a software developed in LabVIEW to establish the communication between the machine and the computer. The main objective of this work is the development of a machine which allows future researches on the process performance, on educational purposes, the demonstration the parts involved on the CNC machine.

This study presents some data-mining experiments applied to electric power systems with the aim of extracting knowledge from historical data produced by the supervision, control and data acquisition system of a hydroelectric plant in Brazil. In the first experiment, statistical analysis is performed on discrete events such as Boolean events, alarms, commands, set-points and analogue quantities as electrical frequency, to display relevant aspects of the electrical system operation. Next, the results of an experiment performed on discrete events from associations describing relationships patterns among items in a database are presented. In the third experiment, a decision tree is used to reveal relationships among several analogue variables as: the relationship between the downstream water level and generated power, for example. In the fourth experiment, a decision tree is designed to detect if the hydro generator operation is violating any constraint imposed by its capability curve, also indicating which limit is extrapolated. These experiences contribute to successfully show the data-mining applicability to power systems, to improve the management of hydroelectric power plants operation, maintenance and planning, besides also contributing to establish a culture of its usage in the electrical industry.

One of the most desired aspects for power suppliers is the acquisition/sale of energy for a future demand. However, power consumption forecast is characterized not only by the variables of the power system itself, but also related to social–economic and climatic factors. Hence, it is imperative for the power suppliers to project and correlate these parameters. This paper presents a study of power load forecast for power suppliers, considering the applicability of wavelets, time series analysis methods and artificial neural networks, for both mid and long term forecasts. Both the periods of forecast are of major importance for power suppliers to define the future power consumption of a given region. The paper also studies the establishment of correlations among the variables using Bayesian networks. The results obtained are much more effective when compared to those projected by the power suppliers based on specialist information. The research discussed here is implemented on a decision support system, contributing to the decision making for acquisition/sale of energy at a future demand; also providing them with new ways for inference and analyses with the correlation model presented here.

In this letter, a methodology is proposed for automatically (and locally) obtaining the shape factor c for the Gaussian basis functions, for each support domain, in order to increase numerical precision and mainly to avoid matrix inversion impossibilities. The concept of calibration function is introduced, which is used for obtaining c. The methodology developed was applied for a 2-D numerical experiment, which results are compared to analytical solution. This comparison revels that the results associated to the developed methodology are very close to the analytical solution for the entire bandwidth of the excitation pulse. The proposed methodology is called in this work Local Shape Factor Calibration Method (LSFCM).

This paper focuses on supplying electrical power for remote communities of the Brazilian Amazon using regional biomass, specifically palm oil biomass, as a primary energy source. The use of Straight Vegetable Oil (SVO) as fuel, is indicated for isolated communities, where the hydro plants or the installation of transmissions line are impracticable. The use of vegetable oils produced in the communities, is a solution when an adequate infrastructure to extracting the oil is available. Brazil is able to use an enormous diversity of vegetable oils, due to a great variety of plants, and the favorable climatic conditions. Technical, economic, environmental and social aspects are analyzed in order to provide a basis for electrical power supply viability in these communities. A case study is presented focused on a typical Brazilian Amazon community located in the State of Pará in order to demonstrate the applicability of the proposed viability strategy.