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PhD researcher in artificial intelligence at University of Regina under the guidance of prof. Kin-Choong Yow. His research is focused on classification of insulators of distribution networks and application of artificial intelligence for fault identification in electrical power systems.
Project Goal: Analyze electrical system components using artificial intelligence, besides metaheuristic techniques.
Current Stage: Working
The contamination on the insulators may increase its surface conductivity and, as a consequence, electrical discharges occur more frequently, which can lead to interruptions in the power supply. To maintain reliability in the electrical distribution power system, components that have lost their insulating properties must be replaced. Identifying the components that need maintenance, is a difficult task as there are several levels of contamination that are hardly noticed during inspections. To improve the quality of inspections, this paper proposes to use the k-nearest neighbours (k-NN) to classify the levels of insulator contamination, based on the image of insulators at various levels of contamination simulated in the laboratory. Using computer vision features such as mean, variance, asymmetry, kurtosis, energy, and entropy are used for training the k-NN. To assess the robustness of the proposed approach, statistical analysis and a comparative assessment with well-consolidated algorithms such as decision tree, ensemble subspace, and support vector machine models are presented. The k-NN showed results of up to 85.17 % accuracy using the k-fold cross-validation method, with an average accuracy higher than 82 % for multi-classification of the contamination of the insulators, being superior to the compared models.
Marcelo Picolotto Corso; Fabio Luis Perez; Stéfano Frizzo Stefenon; Kin-Choong Yow; Raúl García Ovejero; Valderi Reis Quietinho Leithardt. Classification of Contaminated Insulators Using k-Nearest Neighbors Based on Computer Vision. 2021, 1 .
AMA StyleMarcelo Picolotto Corso, Fabio Luis Perez, Stéfano Frizzo Stefenon, Kin-Choong Yow, Raúl García Ovejero, Valderi Reis Quietinho Leithardt. Classification of Contaminated Insulators Using k-Nearest Neighbors Based on Computer Vision. . 2021; ():1.
Chicago/Turabian StyleMarcelo Picolotto Corso; Fabio Luis Perez; Stéfano Frizzo Stefenon; Kin-Choong Yow; Raúl García Ovejero; Valderi Reis Quietinho Leithardt. 2021. "Classification of Contaminated Insulators Using k-Nearest Neighbors Based on Computer Vision." , no. : 1.
Reliability in the supply of electricity depends on isolation from the electrical power system. Insulators are components that have the function of insulating and supporting the electrical grid. The design of electrical distribution network insulators can have a great influence on the distribution of the electric field over its surface. When there is a great intensity of electric field applied specifically in a location, there may be a greater chance of the development of a fault. An optimized insulator profile design can ensure that the network has better performance. In this paper, particle swarm optimization is applied to optimize the profile of an insulator of the conventional electric power grid, based on the electrical potential data obtained using the finite element method, defined in this paper as optimized finite element method. The component parameters are optimized to obtain a parametric model. The parametric model is evaluated and compared with the usually employed profiles to define an optimized design. The results show that the proposed method is a promising alternative for the design of electrical energy distribution insulators.
Stéfano Frizzo Stefenon; Clodoaldo Schutel Furtado Neto; Thiago Spindola Coelho; Ademir Nied; Cristina Keiko Yamaguchi; Kin-Choong Yow. Particle swarm optimization for design of insulators of distribution power system based on finite element method. Electrical Engineering 2021, 1 -8.
AMA StyleStéfano Frizzo Stefenon, Clodoaldo Schutel Furtado Neto, Thiago Spindola Coelho, Ademir Nied, Cristina Keiko Yamaguchi, Kin-Choong Yow. Particle swarm optimization for design of insulators of distribution power system based on finite element method. Electrical Engineering. 2021; ():1-8.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Clodoaldo Schutel Furtado Neto; Thiago Spindola Coelho; Ademir Nied; Cristina Keiko Yamaguchi; Kin-Choong Yow. 2021. "Particle swarm optimization for design of insulators of distribution power system based on finite element method." Electrical Engineering , no. : 1-8.
Contaminated insulators can have higher surface conductivity, which can result in irreversible failures in the electrical power system. In this paper, the ultrasound equipment is used to assist in the prediction of failure identification in porcelain insulators of the 13.8 kV, 60 Hz pin profile. To perform the laboratory analysis, insulators from a problematic branch are removed after an inspection of the electrical system and are evaluated in the laboratory under controlled conditions. To perform the time series predictions, the stacking ensemble learning model is applied with the wavelet transform for signal filtering and noise reduction. For a complete analysis of the model, variations in its configuration were evaluated. The results of root mean square error (RMSE), mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R 2 ) are presented. To validate the result, a benchmarking is presented with well-established models, such as an adaptive neuro-fuzzy inference system (ANFIS) and long-term short-term memory (LSTM).
Stefano Frizzo Stefenon; Matheus Henrique Dal Molin Ribeiro; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho; Valderi Reis Quietinho Leithardt; Luis Augusto Silva; Laio Oriel Seman. Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting. IEEE Access 2021, 9, 66387 -66397.
AMA StyleStefano Frizzo Stefenon, Matheus Henrique Dal Molin Ribeiro, Ademir Nied, Viviana Cocco Mariani, Leandro Dos Santos Coelho, Valderi Reis Quietinho Leithardt, Luis Augusto Silva, Laio Oriel Seman. Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting. IEEE Access. 2021; 9 ():66387-66397.
Chicago/Turabian StyleStefano Frizzo Stefenon; Matheus Henrique Dal Molin Ribeiro; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho; Valderi Reis Quietinho Leithardt; Luis Augusto Silva; Laio Oriel Seman. 2021. "Hybrid Wavelet Stacking Ensemble Model for Insulators Contamination Forecasting." IEEE Access 9, no. : 66387-66397.
Although the skin effect has been widely studied over the years, many of its topics remain unclear for most electrical engineers, including undergraduate students and fresh graduates. Yet, in the cases of application of power frequency current, the knowledge gap to be bridged is more significant. Thus, for contributing to the widening in the knowledge of this effect, this work presents an analysis of the behavior of the current density distribution over the cross-section of differently combined rectangular conductors subject to power frequency current. In this case, since an analytical approach is not feasible, the numerical method of matrix solution of integral equations was adopted due to its simplicity and fast convergence and its application is presented through some providentially chosen theoretical examples before a practical case may be analyzed. As the main results, the influence of a correlated effect that is the proximity effect shows itself as being predominant and the method presents itself as being very convenient for studying the current density distribution in conductors with a cross-section other than the circular, which allow bridging the knowledge gap in this theme. Moreover, the comparison of theoretical cases quite significant. Moreover, the method is adequate to planar configurations, by typical configurations, as in the case of bus bars of electrical panels.
Sergio H. L. Cabral; Savio L. Bertoli; Alessandro Medeiros; Crisleine Regina Hillesheim; Carolina K. De Souza; Stefano Frizzo Stefenon; Ademir Nied; Valderi Reis Quietinho Leithardt; Gabriel Villarrubia Gonzalez. Practical Aspects of the Skin Effect in Low Frequencies in Rectangular Conductors. IEEE Access 2021, 9, 49424 -49433.
AMA StyleSergio H. L. Cabral, Savio L. Bertoli, Alessandro Medeiros, Crisleine Regina Hillesheim, Carolina K. De Souza, Stefano Frizzo Stefenon, Ademir Nied, Valderi Reis Quietinho Leithardt, Gabriel Villarrubia Gonzalez. Practical Aspects of the Skin Effect in Low Frequencies in Rectangular Conductors. IEEE Access. 2021; 9 (99):49424-49433.
Chicago/Turabian StyleSergio H. L. Cabral; Savio L. Bertoli; Alessandro Medeiros; Crisleine Regina Hillesheim; Carolina K. De Souza; Stefano Frizzo Stefenon; Ademir Nied; Valderi Reis Quietinho Leithardt; Gabriel Villarrubia Gonzalez. 2021. "Practical Aspects of the Skin Effect in Low Frequencies in Rectangular Conductors." IEEE Access 9, no. 99: 49424-49433.
Although this is a fact that is not very explored in the literature, there are two possible forms to connect the stator winding of an induction motor in the delta. The choice for one of these forms defines the amplitude of the stator transient current during the switching from star to delta connection when the motor is driven by a star-delta starting system, which is the most widely used and diffused method for starting an induction motor. One of the possible forms of the delta connection gives rise to a switching current with a relatively small amplitude, which gives it the denomination of preferential. The other form has a relatively higher amplitude of switching current, but it is the most recommended and indicated in diagrams of catalogues and motor plates. Therefore, it is here called “common”. With the aim of evidencing how the differences between these two forms of delta connection are manifested, this paper approaches the issue experimentally, through a methodology with statistical support, for a better characterization of the performance of each of these forms of delta connection, in the case of the widely popular star-delta starting method.
José Itajiba; Cézar Varnier; Sergio Cabral; Stéfano Stefenon; Valderi Leithardt; Raúl Ovejero; Ademir Nied; Kin-Choong Yow. Experimental Comparison of Preferential vs. Common Delta Connections for the Star-Delta Starting of Induction Motors. Energies 2021, 14, 1318 .
AMA StyleJosé Itajiba, Cézar Varnier, Sergio Cabral, Stéfano Stefenon, Valderi Leithardt, Raúl Ovejero, Ademir Nied, Kin-Choong Yow. Experimental Comparison of Preferential vs. Common Delta Connections for the Star-Delta Starting of Induction Motors. Energies. 2021; 14 (5):1318.
Chicago/Turabian StyleJosé Itajiba; Cézar Varnier; Sergio Cabral; Stéfano Stefenon; Valderi Leithardt; Raúl Ovejero; Ademir Nied; Kin-Choong Yow. 2021. "Experimental Comparison of Preferential vs. Common Delta Connections for the Star-Delta Starting of Induction Motors." Energies 14, no. 5: 1318.
Interruptions in the supply of electricity cause numerous losses to consumers, whether residential or industrial and may result in fines being imposed on the regulatory agency’s concessionaire. In Brazil, the electrical transmission and distribution systems cover a large territorial area, and because they are usually outdoors, they are exposed to environmental variations. In this context, periodic inspections are carried out on the electrical networks, and ultrasound equipment is widely used, due to non-destructive analysis characteristics. Ultrasonic inspection allows the identification of defective insulators based on the signal interpreted by an operator. This task fundamentally depends on the operator’s experience in this interpretation. In this way, it is intended to test machine learning applications to interpret ultrasound signals obtained from electrical grid insulators, distribution, class 25 kV. Currently, research in the area uses several models of artificial intelligence for various types of evaluation. This paper studies Multilayer Perceptron networks’ application to the classification of the different conditions of ceramic insulators based on a restricted database of ultrasonic signals recorded in the laboratory.
Nemesio Sopelsa Neto; Stéfano Stefenon; Luiz Meyer; Rafael Bruns; Ademir Nied; Laio Seman; Gabriel Gonzalez; Valderi Leithardt; Kin-Choong Yow. A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound. Applied Sciences 2021, 11, 1592 .
AMA StyleNemesio Sopelsa Neto, Stéfano Stefenon, Luiz Meyer, Rafael Bruns, Ademir Nied, Laio Seman, Gabriel Gonzalez, Valderi Leithardt, Kin-Choong Yow. A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound. Applied Sciences. 2021; 11 (4):1592.
Chicago/Turabian StyleNemesio Sopelsa Neto; Stéfano Stefenon; Luiz Meyer; Rafael Bruns; Ademir Nied; Laio Seman; Gabriel Gonzalez; Valderi Leithardt; Kin-Choong Yow. 2021. "A Study of Multilayer Perceptron Networks Applied to Classification of Ceramic Insulators Using Ultrasound." Applied Sciences 11, no. 4: 1592.
The efficiency of electric motors is being improved every day and projects with design variations can improve their performance. Among electric motors, the Permanent Magnet Synchronous Machine (PMSM) is being increasingly used, because of its growing use in electric vehicles. Simulating design variations using the Finite Element Method (FEM) can improve PMSM design, and by optimizing the parameters based on the FEM, even better results can be achieved. The design of the PMSM stator slots must be evaluated, as conductors are accommodated and an electrical potential is applied at this location. The FEM parameters are varied, and the results can be used to build an approximate model, known as a proxy model. The proxy model can then be used in a mathematical programming problem to optimize the design of stators that have less electric field in certain regions, thus reducing the chance of developing a failure. The results of the proposed methodology show that its application is promising for machine design and can also be used for the design of other systems.
Stéfano Frizzo Stefenon; Laio Oriel Seman; Clodoaldo Schutel Furtado Neto; Ademir Nied; Darlan Mateus Seganfredo; Felipe Garcia Da Luz; Pablo Henrique Sabino; José Torreblanca González; Valderi Reis Quietinho Leithardt. Electric Field Evaluation Using the Finite Element Method and Proxy Models for the Design of Stator Slots in a Permanent Magnet Synchronous Motor. Electronics 2020, 9, 1975 .
AMA StyleStéfano Frizzo Stefenon, Laio Oriel Seman, Clodoaldo Schutel Furtado Neto, Ademir Nied, Darlan Mateus Seganfredo, Felipe Garcia Da Luz, Pablo Henrique Sabino, José Torreblanca González, Valderi Reis Quietinho Leithardt. Electric Field Evaluation Using the Finite Element Method and Proxy Models for the Design of Stator Slots in a Permanent Magnet Synchronous Motor. Electronics. 2020; 9 (11):1975.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Laio Oriel Seman; Clodoaldo Schutel Furtado Neto; Ademir Nied; Darlan Mateus Seganfredo; Felipe Garcia Da Luz; Pablo Henrique Sabino; José Torreblanca González; Valderi Reis Quietinho Leithardt. 2020. "Electric Field Evaluation Using the Finite Element Method and Proxy Models for the Design of Stator Slots in a Permanent Magnet Synchronous Motor." Electronics 9, no. 11: 1975.
This article aims to understand the perceptions of young rural entrepreneurs about the difficulties in investing in family farms in which they work. Ninety-eight people were interviewed at the event “Meeting of Young Entrepreneurs of the Rural Environment of Santa Catarina: the rural youth leading the sustainable development”, held in May 2019. The methodology applied in this paper is qualitative and quantitative, through a bibliographic review and a numerical analysis on work conditions and workers’ profile. A brief theoretical background is presented to facilitate the understanding of the results and their relation to family farming, entrepreneurship and its reality in Brazil. As a result, the economic issue was pointed out with 34% of the cases, as a hinter to undertake in rural properties, followed by the lack and low qualification of the workforce available with 12.6% of the cases and the lower selling price for the producer with 7.6% of the cases.
Cristina Keiko Yamaguchi; Stéfano Frizzo Stefenon; Ney Kassiano Ramos; Vanessa Silva Dos Santos; Fernanda Forbici; Anne Carolina Rodrigues Klaar; Fernanda Cristina Silva Ferreira; Alessandra Cassol; Márcio Luiz Marietto; Shana Kimi Farias Yamaguchi; Marcelo Leandro De Borba. Young People’s Perceptions about the Difficulties of Entrepreneurship and Developing Rural Properties in Family Agriculture. Sustainability 2020, 12, 1 .
AMA StyleCristina Keiko Yamaguchi, Stéfano Frizzo Stefenon, Ney Kassiano Ramos, Vanessa Silva Dos Santos, Fernanda Forbici, Anne Carolina Rodrigues Klaar, Fernanda Cristina Silva Ferreira, Alessandra Cassol, Márcio Luiz Marietto, Shana Kimi Farias Yamaguchi, Marcelo Leandro De Borba. Young People’s Perceptions about the Difficulties of Entrepreneurship and Developing Rural Properties in Family Agriculture. Sustainability. 2020; 12 (21):1.
Chicago/Turabian StyleCristina Keiko Yamaguchi; Stéfano Frizzo Stefenon; Ney Kassiano Ramos; Vanessa Silva Dos Santos; Fernanda Forbici; Anne Carolina Rodrigues Klaar; Fernanda Cristina Silva Ferreira; Alessandra Cassol; Márcio Luiz Marietto; Shana Kimi Farias Yamaguchi; Marcelo Leandro De Borba. 2020. "Young People’s Perceptions about the Difficulties of Entrepreneurship and Developing Rural Properties in Family Agriculture." Sustainability 12, no. 21: 1.
To meet the growing electricity demand for consumers, it is necessary to use more efficient systems. The solar trackers stand out among the applications that can improve the efficiency of photovoltaic panel generation by increasing their solar uptake. For solar trackers to be more efficient, they can base their position update on a generation forecast and thus perform the control action only when there is greater efficiency in this update. For generation forecast, the long–short-term memory (LSTM) can handle a large volume of non-linear data. Furthermore, to improve the analysis, it is possible to apply signal filtering techniques. The wavelet energy coefficient is a technique used to reduce signal noise and extract features; this technique performs the filter and preserves the signal characteristic. In this study, the authors present a combination of wavelet energy coefficient and LSTM, defined as wavelet LSTM, to perform photovoltaic power forecasting in the dual-axis solar trackers.
Stéfano Frizzo Stefenon; Christopher Kasburg; Ademir Nied; Anne Carolina Rodrigues Klaar; Fernanda Cristina Silva Ferreira; Nathielle Waldrigues Branco. Hybrid deep learning for power generation forecasting in active solar trackers. IET Generation, Transmission & Distribution 2020, 14, 5667 -5674.
AMA StyleStéfano Frizzo Stefenon, Christopher Kasburg, Ademir Nied, Anne Carolina Rodrigues Klaar, Fernanda Cristina Silva Ferreira, Nathielle Waldrigues Branco. Hybrid deep learning for power generation forecasting in active solar trackers. IET Generation, Transmission & Distribution. 2020; 14 (23):5667-5674.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Christopher Kasburg; Ademir Nied; Anne Carolina Rodrigues Klaar; Fernanda Cristina Silva Ferreira; Nathielle Waldrigues Branco. 2020. "Hybrid deep learning for power generation forecasting in active solar trackers." IET Generation, Transmission & Distribution 14, no. 23: 5667-5674.
Electricity price forecasting plays a vital role in the financial markets. This paper proposes a self-adaptive, decomposed, heterogeneous, and ensemble learning model for short-term electricity price forecasting one, two, and three-months-ahead in the Brazilian market. Exogenous variables, such as supply, lagged prices and demand are considered as inputs signals of the forecasting model. Firstly, the coyote optimization algorithm is adopted to tune the hyperparameters of complementary ensemble empirical mode decomposition in the pre-processing phase. Next, three machine learning models, including extreme learning machine, gradient boosting machine, and support vector regression models, as well as Gaussian process, are designed with the intent of handling the components obtained through the signal decomposition approach with focus on time series forecasting. The individual forecasting models are directly integrated in order to obtain the final forecasting prices one to three-months-ahead. In this case, a grid of forecasting models is obtained. The best forecasting model is the one that has better generalization out-of-sample. The empirical results show the efficiency of the proposed model. Additionally, it can achieve forecasting errors lower than 4.2% in terms of symmetric mean absolute percentage error. The ranking of importance of the variables, from the smallest to the largest is, lagged prices, demand, and supply. This paper provided useful insights for multi-step-ahead forecasting in the electrical market, once the proposed model can enhance forecasting accuracy and stability.
Matheus Henrique Dal Molin Ribeiro; Stéfano Frizzo Stefenon; José Donizetti De Lima; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho. Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning. Energies 2020, 13, 5190 .
AMA StyleMatheus Henrique Dal Molin Ribeiro, Stéfano Frizzo Stefenon, José Donizetti De Lima, Ademir Nied, Viviana Cocco Mariani, Leandro Dos Santos Coelho. Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning. Energies. 2020; 13 (19):5190.
Chicago/Turabian StyleMatheus Henrique Dal Molin Ribeiro; Stéfano Frizzo Stefenon; José Donizetti De Lima; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho. 2020. "Electricity Price Forecasting Based on Self-Adaptive Decomposition and Heterogeneous Ensemble Learning." Energies 13, no. 19: 5190.
O presente artigo tem como objetivo apresentar uma análise técnica sobre a tecnologia PLC (Power Line Communication) em ambientes indoor e suas principais caracteristicas. Descreve os reais resultados desta tecnologia na prática apresentando as vantagens e desvantagens do seu uso no meio físico. Com o avanço desta tecnologia, podemos observar que o baixo custo para implementação vem tornando a tecnologia PLC uma excelente opção para muitas pessoas no uso doméstico da internet, portanto se utilizada em ambientes adequados é possível obter uma economia em energia elétrica significativa. Deste modo, os avanços desta tecnologia estão aumentando sua proteção contra interferências e ruídos na rede elétrica, fazendo com que se torne uma das tecnologias mais promissoras quanto ao uso de internet em ambientes residenciais. Com o intuito de viabilizar esta tecnologia, foi elaborada uma proposta de implementação no bloco de engenharias da UNIPLAC (Universidade do Planalto Catarinense), propondo um resultado semelhante a rede convencional cabeada, porém com um custo extremamente baixo para instalação e manutenção.
Fabricio Leonardo Ribeiro; Rafael Gattino Furtado; Stéfano Frizzo Stefenon; Graciela Alessandra Dela Rocca; Gabriel Constante Carvalho. AVALIAÇÃO TÉCNICA E DE VIABILIDADE ECONÔMICA DA UTILIZAÇÃO DA TECNOLOGIA PLC. Conexões - Ciência e Tecnologia 2020, 14, 74 -83.
AMA StyleFabricio Leonardo Ribeiro, Rafael Gattino Furtado, Stéfano Frizzo Stefenon, Graciela Alessandra Dela Rocca, Gabriel Constante Carvalho. AVALIAÇÃO TÉCNICA E DE VIABILIDADE ECONÔMICA DA UTILIZAÇÃO DA TECNOLOGIA PLC. Conexões - Ciência e Tecnologia. 2020; 14 (3):74-83.
Chicago/Turabian StyleFabricio Leonardo Ribeiro; Rafael Gattino Furtado; Stéfano Frizzo Stefenon; Graciela Alessandra Dela Rocca; Gabriel Constante Carvalho. 2020. "AVALIAÇÃO TÉCNICA E DE VIABILIDADE ECONÔMICA DA UTILIZAÇÃO DA TECNOLOGIA PLC." Conexões - Ciência e Tecnologia 14, no. 3: 74-83.
Electric power is increasingly being used in the globalized day-to-day and keeping the electric power system running is necessary. Insulators are important components of the electric power system. In case of failure in these components, there may be disconnections and, consequently, no electricity. Contaminated insulators can develop irreversible failures if they are not inspected. One equipment used for the inspection of the electric power system is the ultrasound, which generates an audible noise based on a time series that is used to identify possible failures. The time series forecast can be used for possible prediction of the development of failure. In this paper, a hybrid method that uses Wavelet Energy Coefficient (WEC) for feature extraction and Group Method of Data Handling (GMDH) for time series prediction is proposed, being defined as Wavelet GMDH. For comparison and validation of the proposed method, a benchmark is made with well-established algorithms such as Long Short-Term Memory (LSTM) and Adaptive Neuro-Fuzzy Inference System (ANFIS). For a fairer analysis, these algorithms are also evaluated based on the same data extraction with WEC. The proposed method proved to have good accuracy comparing with LSTM and ANFIS, and is much faster than the compared methods.
Stéfano Frizzo Stefenon; Matheus Henrique Dal Molin Ribeiro; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho; Diovana Fátima Menegat da Rocha; Rafael Bartnik Grebogi; António Eduardo De Barros Ruano. Wavelet group method of data handling for fault prediction in electrical power insulators. International Journal of Electrical Power & Energy Systems 2020, 123, 106269 .
AMA StyleStéfano Frizzo Stefenon, Matheus Henrique Dal Molin Ribeiro, Ademir Nied, Viviana Cocco Mariani, Leandro Dos Santos Coelho, Diovana Fátima Menegat da Rocha, Rafael Bartnik Grebogi, António Eduardo De Barros Ruano. Wavelet group method of data handling for fault prediction in electrical power insulators. International Journal of Electrical Power & Energy Systems. 2020; 123 ():106269.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Matheus Henrique Dal Molin Ribeiro; Ademir Nied; Viviana Cocco Mariani; Leandro Dos Santos Coelho; Diovana Fátima Menegat da Rocha; Rafael Bartnik Grebogi; António Eduardo De Barros Ruano. 2020. "Wavelet group method of data handling for fault prediction in electrical power insulators." International Journal of Electrical Power & Energy Systems 123, no. : 106269.
This paper is intended to perform a comparative and qualitative review among eight tools to measure energy sustainability. Therefore, it was necessary to create a theoretical and conceptual framework based on four criterias of selection and six categories of comparison. In this work, the conceptual bases that supported the research and the methodology created to carry out the comparative review will be presented. This analysis was based on the intrinsic concepts of energy sustainability of each of the reviewed tools with a critical qualitative analysis. Some conclusions shown through the conceptual framework developed that it was possible to apply an innovative methodology to qualitatively compare different tools to measure sustainability. The importance of this reflects the difficulty of conceptualizing the subjectivity of sustainable development, as shown throughout the paper, where it is often not possible to obtain a measurable result since the measured phenomenon is too complex to reduce it to a numerical value.
Rafael Ninno Muniz; Stéfano Frizzo Stefenon; William Gouvêa Buratto; Ademir Nied; Luiz Henrique Meyer; Erlon Cristian Finardi; Ricardo Marino Kühl; José Alberto Silva De Sá; Brigida Ramati Pereira Da Rocha. Tools for Measuring Energy Sustainability: A Comparative Review. Energies 2020, 13, 2366 .
AMA StyleRafael Ninno Muniz, Stéfano Frizzo Stefenon, William Gouvêa Buratto, Ademir Nied, Luiz Henrique Meyer, Erlon Cristian Finardi, Ricardo Marino Kühl, José Alberto Silva De Sá, Brigida Ramati Pereira Da Rocha. Tools for Measuring Energy Sustainability: A Comparative Review. Energies. 2020; 13 (9):2366.
Chicago/Turabian StyleRafael Ninno Muniz; Stéfano Frizzo Stefenon; William Gouvêa Buratto; Ademir Nied; Luiz Henrique Meyer; Erlon Cristian Finardi; Ricardo Marino Kühl; José Alberto Silva De Sá; Brigida Ramati Pereira Da Rocha. 2020. "Tools for Measuring Energy Sustainability: A Comparative Review." Energies 13, no. 9: 2366.
The article investigates the strategies used by Distance Education (DE) tutors to mobilize students in carrying out the activities available in the Virtual Learning Environment. To reflect on the mobility of tutors, learning theories outlined for Distance Education were revisited. The methodology consisted of a study applied at a university in southern Brazil. As a data collection instrument, a questionnaire was developed and applied to a group of tutor professors who work in DE. The testimonies obtained were analyzed to show the strategies used to mobilize students in the perspective of meaningful learning. The analysis showed that the terms mobilization and motivation are used interchangeably; the dimensions of meaningful learning (active, authentic, cooperation, constructive and intentional) are used to mobilize students, but not all dimensions have been captured in digital reports. This can be indicative of prioritizing one dimension over another. It was concluded that further investigations should be carried out to demystify the tutor's strategies regarding learning theories.
Madalena Pereira Da Silva; Marina Patrício De Arruda; Marlene Zwierewicz; Stéfano Frizzo Stefenon; Fernanda Cristina Silva Ferreira; Anne Carolina Rodrigues Klaar; Cristina Keiko Yamaguchi; Alexandre Tripoli Venção; Rodrigo Branco; Diogo Felipe Steinheuser. THE MOBILITY OF PROFESSORS IN PERFORMING DISTANCE EDUCATION ACTIVITIES. International Journal for Innovation Education and Research 2020, 8, 514 -526.
AMA StyleMadalena Pereira Da Silva, Marina Patrício De Arruda, Marlene Zwierewicz, Stéfano Frizzo Stefenon, Fernanda Cristina Silva Ferreira, Anne Carolina Rodrigues Klaar, Cristina Keiko Yamaguchi, Alexandre Tripoli Venção, Rodrigo Branco, Diogo Felipe Steinheuser. THE MOBILITY OF PROFESSORS IN PERFORMING DISTANCE EDUCATION ACTIVITIES. International Journal for Innovation Education and Research. 2020; 8 (4):514-526.
Chicago/Turabian StyleMadalena Pereira Da Silva; Marina Patrício De Arruda; Marlene Zwierewicz; Stéfano Frizzo Stefenon; Fernanda Cristina Silva Ferreira; Anne Carolina Rodrigues Klaar; Cristina Keiko Yamaguchi; Alexandre Tripoli Venção; Rodrigo Branco; Diogo Felipe Steinheuser. 2020. "THE MOBILITY OF PROFESSORS IN PERFORMING DISTANCE EDUCATION ACTIVITIES." International Journal for Innovation Education and Research 8, no. 4: 514-526.
Identifying defects in electrical power systems during field inspections is a difficult task, since faults are generally not visible and may be intermittent. To find possible adverse conditions, specific inspection equipment is used. The ultrasound detector is the equipment normally used to inspect outdoor insulating systems; however, using it demands operator experience. To improve the defect condition classification, artificial intelligence techniques are applied to assist the operator in the decision task and thereby facilitate the identification of faulty insulating devices in the grid. The training of artificial neural network (ANN) models is an important step in solving the classification problem. This study aims to evaluate the training capacity in terms of the performance of different optimisation methods for the calculation of the mean square error after convergence. Traditional methods such as Gradient Descent and its variations will be presented, as well as methods that employ high computational effort such as quasi-Newton and Levenberg–Marquardt. In order to base these concepts, a review will be presented on the use of these algorithms and on the problem of classification of insulators in distribution networks. The results show that there is a considerable performance difference between the calculation methods.
Stéfano Frizzo Stefenon; Nathielle Waldrigues Branco; Ademir Nied; Douglas Wildgrube Bertol; Erlon Cristian Finardi; Andreza Sartori; Luiz Henrique Meyer; Rafael Bartnik Grebogi. Analysis of training techniques of ANN for classification of insulators in electrical power systems. IET Generation, Transmission & Distribution 2020, 14, 1591 -1597.
AMA StyleStéfano Frizzo Stefenon, Nathielle Waldrigues Branco, Ademir Nied, Douglas Wildgrube Bertol, Erlon Cristian Finardi, Andreza Sartori, Luiz Henrique Meyer, Rafael Bartnik Grebogi. Analysis of training techniques of ANN for classification of insulators in electrical power systems. IET Generation, Transmission & Distribution. 2020; 14 (8):1591-1597.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Nathielle Waldrigues Branco; Ademir Nied; Douglas Wildgrube Bertol; Erlon Cristian Finardi; Andreza Sartori; Luiz Henrique Meyer; Rafael Bartnik Grebogi. 2020. "Analysis of training techniques of ANN for classification of insulators in electrical power systems." IET Generation, Transmission & Distribution 14, no. 8: 1591-1597.
The surface contamination of electrical insulators can increase the electrical conductivity of these components, which may lead to faults in the electrical power system. During inspections, ultrasound equipment is employed to detect defective insulators or those that may cause failures within a certain period. Assuming that the signal collected by the ultrasound device can be processed and used for both the detection of defective insulators and prediction of failures, this study starts by presenting an experimental procedure considering a contaminated insulator removed from the distribution line for data acquisition. Based on the obtained data set, an offline time series forecasting approach with an Adaptive Neuro-Fuzzy Inference System (ANFIS) was conducted. To improve the time series forecasting performance and to reduce the noise, Wavelet Packets Transform (WPT) was associated to the ANFIS model. Once the ANFIS model associated with WPT has distinct parameters to be adjusted, a complete evaluation concerning different model configurations was conducted. In this case, three inference system structures were evaluated: grid partition, fuzzy c-means clustering, and subtractive clustering. A performance analysis focusing on computational effort and the coefficient of determination provided additional parameter configurations for the model. Taking into account both parametrical and statistical analysis, the Wavelet Neuro-Fuzzy System with fuzzy c-means showed that it is possible to achieve impressive accuracy, even when compared to classical approaches, in the prediction of electrical insulators conditions.
Stéfano Frizzo Stefenon; Roberto Zanetti Freire; Leandro Dos Santos Coelho; Luiz Henrique Meyer; Rafael Bartnik Grebogi; William Gouvêa Buratto; Ademir Nied. Electrical Insulator Fault Forecasting Based on a Wavelet Neuro-Fuzzy System. Energies 2020, 13, 484 .
AMA StyleStéfano Frizzo Stefenon, Roberto Zanetti Freire, Leandro Dos Santos Coelho, Luiz Henrique Meyer, Rafael Bartnik Grebogi, William Gouvêa Buratto, Ademir Nied. Electrical Insulator Fault Forecasting Based on a Wavelet Neuro-Fuzzy System. Energies. 2020; 13 (2):484.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Roberto Zanetti Freire; Leandro Dos Santos Coelho; Luiz Henrique Meyer; Rafael Bartnik Grebogi; William Gouvêa Buratto; Ademir Nied. 2020. "Electrical Insulator Fault Forecasting Based on a Wavelet Neuro-Fuzzy System." Energies 13, no. 2: 484.
The generation of electricity by photovoltaic panels depends on the position of solar incidence on them. Using active solar trackers may be a maximization of generating capacity. However, if motors that update the position of the panels use more energy than the efficiency in their use, the system becomes ineffective. In this way, solar forecasting can be used to actively determine the generation capacity and to assess whether position updating is efficient. Among the algorithms that can be used to predict photovoltaic generation, stands out the Long Short-Term Memory (LSTM) which is an artificial recurrent neural network architecture used in deep learning. This technique stands out among the others for having the ability to handle complex problems with high nonlinearity. The results of the application of LSTM for photovoltaic generation forecast in active solar trackers are promising as described in this article.
Christopher Kasburg; Stefano Frizzo Stefenon. Deep Learning for Photovoltaic Generation Forecast in Active Solar Trackers. IEEE Latin America Transactions 2019, 17, 2013 -2019.
AMA StyleChristopher Kasburg, Stefano Frizzo Stefenon. Deep Learning for Photovoltaic Generation Forecast in Active Solar Trackers. IEEE Latin America Transactions. 2019; 17 (12):2013-2019.
Chicago/Turabian StyleChristopher Kasburg; Stefano Frizzo Stefenon. 2019. "Deep Learning for Photovoltaic Generation Forecast in Active Solar Trackers." IEEE Latin America Transactions 17, no. 12: 2013-2019.
Stéfano Frizzo Stefenon; Marcelo Campos Silva; Douglas Wildgrube Bertol; Luiz Henrique Meyer; Ademir Nied. Fault diagnosis of insulators from ultrasound detection using neural networks. Journal of Intelligent & Fuzzy Systems 2019, 37, 6655 -6664.
AMA StyleStéfano Frizzo Stefenon, Marcelo Campos Silva, Douglas Wildgrube Bertol, Luiz Henrique Meyer, Ademir Nied. Fault diagnosis of insulators from ultrasound detection using neural networks. Journal of Intelligent & Fuzzy Systems. 2019; 37 (5):6655-6664.
Chicago/Turabian StyleStéfano Frizzo Stefenon; Marcelo Campos Silva; Douglas Wildgrube Bertol; Luiz Henrique Meyer; Ademir Nied. 2019. "Fault diagnosis of insulators from ultrasound detection using neural networks." Journal of Intelligent & Fuzzy Systems 37, no. 5: 6655-6664.
The application of software for the design of electrical equipment has been increasingly used to improve its efficiency. In the project of electric motors the definition of the design of the stator slots is an extremely important feature, since the stator windings are accommodated in this place and for this reason there is a large concentration of electric field. The electric field intensity is usually associated with the presence of faults and must therefore be investigated. Through the Finite Element Method (FEM) it is possible to simulate electric field on surfaces and different geometries. In this paper, an evaluation of electric field will be presented through the variations of design of the stator slots of a Permanent-Magnet Synchronous Machine (PMSM) to evaluate the most efficient profile for this application.
S. Stefenon; Ademir Nied. FEM Applied to Evaluation of the Influence of Electric Field on Design of the Stator Slots in PMSM. IEEE Latin America Transactions 2019, 17, 590 -596.
AMA StyleS. Stefenon, Ademir Nied. FEM Applied to Evaluation of the Influence of Electric Field on Design of the Stator Slots in PMSM. IEEE Latin America Transactions. 2019; 17 (04):590-596.
Chicago/Turabian StyleS. Stefenon; Ademir Nied. 2019. "FEM Applied to Evaluation of the Influence of Electric Field on Design of the Stator Slots in PMSM." IEEE Latin America Transactions 17, no. 04: 590-596.