Takaaki Ohishi - Academia.edu (original) (raw)

Papers by Takaaki Ohishi

The soybean exporter chain has high participation in the economic performance of the country. How... more The soybean exporter chain has high participation in the economic performance of the country. However, the main producing areas are exposed to several logistical problems arising from lack of planning and investment in infrastructure. As a result, producers are burdened by the costs and have an available capital decrease to future investments, which reduce futures crops and future economic potential of the country. Faced with this reality, the Brazilian government has taken measures and investing to solve these problems. Investments in infrastructure should be planned for the long term. Thus, this paper proposes the analysis of a capacitated model design of network hubs and then, based on it, develops three mathematical models that describe the soybeans exporter chain, in order to create an analysis tool to define the location of facilities, as storage / switching / transshipment facilities, define routes and ports that should be utilized to optimize the use of the chain. In order to apply the model, the state of Mato Grosso was selected as the focus of this study and, based on which, an extensive survey data of soybeans was realized. Whereas that the State of Mato Grosso is divided into 22 micro regions it was estimated their soybeans production, identified the amount of soybeans exported and the static capacity to each one. The main importer's countries of Brazilian soybeans and the major export ports it was also identified, in addition, the amounts of soybeans exported by each country and ports, and identification of routes and sea routes used to transport.

Em sistemas elétricos, um dos principais fatores limitantes do transporte de energia é a temperat... more Em sistemas elétricos, um dos principais fatores limitantes do transporte de energia é a temperatura do condutor. Conhecendo-se a potência transportada através do sistema de transmissão, suas linhas, as seções mais críticas e o clima da região onde se encontram, podemos calcular a temperatura real do condutor, proporcionando em determinadas condições, um aumento da capacidade de transmissão, sem comprometer a segurança operacional. Como no projeto da linha de transmissão a sua capacidade é baseada em estimativas muito conservadoras, uma linha aparentemente sobrecarregada poderia causar em alguns momentos, uma alteração desnecessária no despacho dos geradores e nos demais controles do sistema. Nesta tese são propostos dois estudos de influências das condições climáticas no despacho da operação. A primeira considera os limites na transmissão como sendo variáveis e dependentes das condições climáticas a que estão submetidos. A segunda forma de operação utiliza como dados de entrada para o despacho as resistências das linhas de transmissão atualizadas pela sua temperatura de operação.

A Deus, em primeiro lugar, por sempre estar comigo nas horas mais difíceis. Ao Professor Takaaki ... more A Deus, em primeiro lugar, por sempre estar comigo nas horas mais difíceis. Ao Professor Takaaki Ohishi pela sua grande orientação, apoio e ajuda. À minha família pelo carinho, apoio e incentivo, apesar da distância. Às amigas Luciana e Rosângela por todo incentivo, carinho e ajuda. Aos amigos Makoto, Arce, Adriana e Leonardo pela amizade e convívio. Aos demais amigos do Cose. Aos amigos Oderson e Sérgio pela amizade e ajuda na organização deste trabalho. À CAPES pelo suporte financeiro deste trabalho. À FAPESP e a Duke Energy International. E a todos que, de alguma forma, contribuíram para o desenvolvimento deste trabalho. v Resumo Esta dissertação de Mestrado objetiva o desenvolvimento de uma metodologia para o problema de Pré-Despacho, a qual consiste na determinação de um programa de operação das unidades geradoras de um sistema de energia elétrica para um horizonte de curto prazo. A metodologia foi aplicada a um sistema hidrelétrico e utilizou iterativamente um modelo de Despacho de Máquinas, solucionado através de Algoritmos Genéticos, e um modelo de Despacho de Geração, resolvido com Relaxação Lagrangeana. O Despacho de Máquinas é responsável pela definição dos grupos geradores que estarão em operação em cada intervalo de tempo, tratando-se assim de um problema combinatório, o que justifica o uso de um Algoritmo Genético. Em seguida, depois de definida a configuração de máquinas em operação, o Despacho de Geração soluciona um problema formulado somente com variáveis reais. A função aptidão (fitness) do modelo de Algoritmo Genético leva em conta os custos de partida e as perdas nas usinas hidrelétricas. A metodologia foi aplicada a um caso real do Sistema de usinas Hidrelétricas do rio Paranapanema. Para tornar aplicação amigável foi desenvolvido um programa computacional, o qual integra a metodologia de pré-despacho com uma interface em ambiente windows. Essa interface possibilita a definição da quantidade de usinas que devem operar, a configuração do algoritmo de despacho de máquinas, além da visualização de gráficos e tabelas. O programa foi implementado em linguagem de programação C++, usando a plataforma de programação Builder

Revista de Ciências Gerenciais, Aug 23, 2012

Applied Sciences

The greater flow of containers in global supply chains requires ever-increasing productivity at p... more The greater flow of containers in global supply chains requires ever-increasing productivity at port terminals. The research found in the literature has focused on optimizing specific parts of port operations but has ignored important features, such as the stack-wise organization of containers in a container ship and port yard and the effects of interconnection among the operations in both places. The objective of this paper is to show the importance of designing an integrated plan of the container relocation problem at the port yard with the stowage planning problem for loading and unloading a ship through ports. Both individual problems are NP-Complete, and exact approaches for each problem are only able to find optimal or feasible solutions for small instances. We describe a simulation-optimization methodology that combines simulation, a genetic algorithm, and a new solution representation based on rules. The test results show that the solution from the integrated plan is mutuall...

Avanços em Ciência e Tecnologia de Alimentos - Volume 5, 2021

In a power operation system there are many variables that can influence the execution of the cont... more In a power operation system there are many variables that can influence the execution of the control routines. The attendance of these variables is very important to aid the processes in the safe operation of the system. In the electric system the bus load level is an important variable in the operation planning step. Accurate information on the load level in each bus provide a better control in the power flow, safe and security analysis, operation programming, planning and others. Thus, this work presents two contributions to the bus load forecasting area. The first contribution is the development of a bus load forecast methodology that executes and provides the forecast results for several buses in an aggregate way. The second contribution is a computational system for bus load forecasting named SysPrev-Support System for Bus Load Analysis and Forecasting-developed to facilitate the bus load forecasting process. The aggregate bus load forecasting model is composed by two steps: In the first phase a clustering algorithm is used to identify buses clusters with similar daily load profile and in the second phase is proposed an aggregate structure for to foresee each bus using a conventional prediction model. The SysPrev is a software composed of a data manager subsystem, a model subsystem and a graphical interfaces subsystem. The data manager subsystem is composed of a database that contains bus load time series and other relevant information. The model subsystem is composed of forecasting and clustering techniques. To facilitate the user's interaction, the graphical interface has packages of graphic windows that provide a friendly environment facilitating the integration of the SysPrev and their users. An excellent characteristic of the SysPrev is its construction based on components plug-and-play that allows the insert of new functionalities. With this architecture, each component is produced on an independent way, could be inserted in the software without alterations in the main system. This factor is important, because it supplies the user with the option of customizing and crevii ating new analysis tools, facilitating the updating and the maintenance of the system. The SysPrev was applied to a real power system data composed of 73 buses. The easiness of creating multiple sceneries made possible the fast understanding of the data providing good results in the forecasts, making possible larger precision on the power system operation step.

The Brazilian Power System supplies around 97 % of national energy demand. By reason of the broad... more The Brazilian Power System supplies around 97 % of national energy demand. By reason of the broad Brazilian territory, it requires a transmission system of large scale, due to the large distances between the generations of hydropower and the main concentration of demand that stay in southeastern of Brazil. To ensure security and economy of operation of the Brazilian Electric System are performed analyzes the operation of generation and transmission system due to the conditions of critical loads. The idea is to prepare the system to resist the harshest load conditions. The curve of critical load is calculated for each month with hourly discretization (or less). It's made with the minimum load observed in a given month between the first to eighth hour, and to maximum load observed in the month for the rest of hours. Using the demand agents' history belonging to the Brazilian Power System, it was possible to create a record of five years, 60 months, of curves of critical load. These datas were available by the National Operator of the Brazilian Power System as part of the development of a research project, made available by a decision support system named SysPrev. This dissertation proposed three models to perform the forecasting of the critical load curve. Two models using Artificial Neural Networks and one model using Exponential Smoothing Holt-Winters (HW). The results obtained by all the models were satisfactory and compatible with existing procedures. The exponential smoothing model stood out against the other two models, this having absolute average errors near 3%. These results are justified due to the historical series of curves of critical load has characteristics of trend and seasonality and the HW model is specifically designed for time series with such characteristics.

XXIV Congresso de Iniciação Científica da Unicamp, 2016

Resumo A partir da análise das Cinco Forças de Porter sobre a indústria de bebidas brasileira, é ... more Resumo A partir da análise das Cinco Forças de Porter sobre a indústria de bebidas brasileira, é possível ter um panorama geral e montar uma estratégia para empresas entrantes. Observa-se uma oportunidade de construir uma empresa startup para oferecer a esses entrantes uma solução de eficiência logística para auxiliar e otimizar a decisão de construção de novas plantas de manufatura de bebidas, inicialmente levando em conta os custos logísticos inbound e outbound.

Third International Conference on Natural Computation (ICNC 2007), 2007

ABSTRACT Short-term load forecasting (STLF) has always been a very important issue in power syste... more ABSTRACT Short-term load forecasting (STLF) has always been a very important issue in power system planning and operation. Recently, along with power system privatization and deregulation, accurate forecast of electricity load has received increasing attention. However, forecasting electricity load is difficult because of the randomness and uncertainties of load demand. Support vector machine (SVM) is a novel type of learning machine, which has been successfully employed to solve nonlinear regression and time series problems and showed its potential in STLF. However, the accuracy of STLF is greatly related to the selected parameters of SVM. In this paper, the SCE-UA algorithm, which is an effective and efficient method to optimize model parameters and widely applied to optimize the parameters of the hydrologic models, is employed to optimize the parameters of a SVM model. Subsequently, examples of electricity load data from GuiZhou Power Grid, China were used to compare the forecast performance of the proposed SCE-UA SVM model and back propagation neural network(BPNN) which has obtained wide attention in STLF . The results reveal that the proposed model outperforms the BPNN model. Consequently, the proposed SCE-UA SVM model provides a promising alternative for forecasting electricity load.

Energies

Electric power systems have experienced the rapid insertion of distributed renewable generating s... more Electric power systems have experienced the rapid insertion of distributed renewable generating sources and, as a result, are facing planning and operational challenges as new grid connections are made. The complexity of this management and the degree of uncertainty increase significantly and need to be better estimated. Considering the high volatility of photovoltaic generation and its impacts on agents in the electricity sector, this work proposes a multivariate strategy based on design of experiments (DOE), principal component analysis (PCA), artificial neural networks (ANN) that combines the resulting outputs using Mixture DOE (MDOE) for photovoltaic generation prediction a day ahead. The approach separates the data into seasons of the year and considers multiple climatic variables for each period. Here, the dimensionality reduction of climate variables is performed through PCA. Through DOE, the possibilities of combining prediction parameters, such as those of ANN, were reduced...

2017 IEEE 7th International Conference on Power and Energy Systems (ICPES)

The very short-term bus reactive load forecasting allows the electrical system operator to determ... more The very short-term bus reactive load forecasting allows the electrical system operator to determine the optimal amount of energy to supply the demand with quality, safety and reliability. With this premise, this paper used a knowledge data discovery approach to handle the forecast, from raw data to results analysis, using the neural network for data mining. Two forecasting models were developed: the individual model using only your historical data; and the clustered model using data from other similar buses. The models were applied to Brazilian power system bus data. The results were analyzed according to the error and the confidence level of the forecast.

This paper introduces a new optimization model that integrates the multi-port stowage planning pr... more This paper introduces a new optimization model that integrates the multi-port stowage planning problem with the container relocation problem. This problem is formulated as a binary mathematical programming model that must find the containers' move sequence so that the number of relocations during the whole journey of a ship, as well as the associated port yards is minimized. Modeling by binary variables to represent the cargo status in a ship and yards makes the problem very complex to be solved by exact methods. To the best of our knowledge, this integrated model has not been developed yet as that such problems are always addressed in a partitioned or hierarchical way. A demonstration of the benefits of an integrated approach is given. The model is solved in two different commercial solvers and the results for randomly generated instances are presented and compared to the hierarchical approach. Two heuristics approaches are proposed to quickly generate feasible solutions for warm-starting the model. Extensive computational tests are performed and the results indicate that the solution approaches can reach optimal solutions for small sized instances and good quality solutions on real-scale based instances within reasonable computation time. This is a promising model to support decisions in

Esta tese apresenta um modelo de programacao da operacao de sistemas hidreletricos com restricao ... more Esta tese apresenta um modelo de programacao da operacao de sistemas hidreletricos com restricao de seguranca. A seguranca operacional e um dos aspectos mais importantes na operacao de sistema de energia eletrica, porque a maior parte das faltas no fornecimento de energia eletrica acontece devido a eventos inesperados, como saidas forcadas de equipamentos. A finalidade de um modelo de programacao da operacao de sistemas hidreletricos e definir uma programacao de partidas e paradas das unidades geradoras e os despachos de geracao de energia para os proximos dias. A formulacao matematica do problema resulta em um problema de otimizacao inteira mista nao-linear, que foi tratada por uma abordagem hibrida, combinando o metodo do caminho minimo, o metodo de Newton, a tecnica de conjunto ativo e uma analise de seguranca. O modelo foi aplicado em um estudo de caso baseado no Sistema Interligado Brasileiro. Abstract

Uma das atividades principais na aprendizagem eletronica e o desenvolvimento de conteudo. Este co... more Uma das atividades principais na aprendizagem eletronica e o desenvolvimento de conteudo. Este conteudo pode ser de varios tipos: textos, sons, imagens, animacoes, videos, entre outros. Diante da necessidade de reutilizacao e compartilhamento de informacao na forma de arquivos de diversos tipos por alunos e professores, torna-se relevante investigar novas formas de se aumentar a produtividade durante a autoria ao mesmo tempo em que se busca o favorecimento da aprendizagem. Entre os objetivos pedagogicos do aplicativo desenvolvido, destaca-se o fato deste permitir o trabalho com mapas conceituais, diagramas que buscam favorecer a aprendizagem significativa, a qual guarda forte relacao com criatividade e inovacao, temas de importância na Educacao em Engenharia atual.

The soybean exporter chain has high participation in the economic performance of the country. How... more The soybean exporter chain has high participation in the economic performance of the country. However, the main producing areas are exposed to several logistical problems arising from lack of planning and investment in infrastructure. As a result, producers are burdened by the costs and have an available capital decrease to future investments, which reduce futures crops and future economic potential of the country. Faced with this reality, the Brazilian government has taken measures and investing to solve these problems. Investments in infrastructure should be planned for the long term. Thus, this paper proposes the analysis of a capacitated model design of network hubs and then, based on it, develops three mathematical models that describe the soybeans exporter chain, in order to create an analysis tool to define the location of facilities, as storage / switching / transshipment facilities, define routes and ports that should be utilized to optimize the use of the chain. In order to apply the model, the state of Mato Grosso was selected as the focus of this study and, based on which, an extensive survey data of soybeans was realized. Whereas that the State of Mato Grosso is divided into 22 micro regions it was estimated their soybeans production, identified the amount of soybeans exported and the static capacity to each one. The main importer's countries of Brazilian soybeans and the major export ports it was also identified, in addition, the amounts of soybeans exported by each country and ports, and identification of routes and sea routes used to transport.

Em sistemas elétricos, um dos principais fatores limitantes do transporte de energia é a temperat... more Em sistemas elétricos, um dos principais fatores limitantes do transporte de energia é a temperatura do condutor. Conhecendo-se a potência transportada através do sistema de transmissão, suas linhas, as seções mais críticas e o clima da região onde se encontram, podemos calcular a temperatura real do condutor, proporcionando em determinadas condições, um aumento da capacidade de transmissão, sem comprometer a segurança operacional. Como no projeto da linha de transmissão a sua capacidade é baseada em estimativas muito conservadoras, uma linha aparentemente sobrecarregada poderia causar em alguns momentos, uma alteração desnecessária no despacho dos geradores e nos demais controles do sistema. Nesta tese são propostos dois estudos de influências das condições climáticas no despacho da operação. A primeira considera os limites na transmissão como sendo variáveis e dependentes das condições climáticas a que estão submetidos. A segunda forma de operação utiliza como dados de entrada para o despacho as resistências das linhas de transmissão atualizadas pela sua temperatura de operação.

A Deus, em primeiro lugar, por sempre estar comigo nas horas mais difíceis. Ao Professor Takaaki ... more A Deus, em primeiro lugar, por sempre estar comigo nas horas mais difíceis. Ao Professor Takaaki Ohishi pela sua grande orientação, apoio e ajuda. À minha família pelo carinho, apoio e incentivo, apesar da distância. Às amigas Luciana e Rosângela por todo incentivo, carinho e ajuda. Aos amigos Makoto, Arce, Adriana e Leonardo pela amizade e convívio. Aos demais amigos do Cose. Aos amigos Oderson e Sérgio pela amizade e ajuda na organização deste trabalho. À CAPES pelo suporte financeiro deste trabalho. À FAPESP e a Duke Energy International. E a todos que, de alguma forma, contribuíram para o desenvolvimento deste trabalho. v Resumo Esta dissertação de Mestrado objetiva o desenvolvimento de uma metodologia para o problema de Pré-Despacho, a qual consiste na determinação de um programa de operação das unidades geradoras de um sistema de energia elétrica para um horizonte de curto prazo. A metodologia foi aplicada a um sistema hidrelétrico e utilizou iterativamente um modelo de Despacho de Máquinas, solucionado através de Algoritmos Genéticos, e um modelo de Despacho de Geração, resolvido com Relaxação Lagrangeana. O Despacho de Máquinas é responsável pela definição dos grupos geradores que estarão em operação em cada intervalo de tempo, tratando-se assim de um problema combinatório, o que justifica o uso de um Algoritmo Genético. Em seguida, depois de definida a configuração de máquinas em operação, o Despacho de Geração soluciona um problema formulado somente com variáveis reais. A função aptidão (fitness) do modelo de Algoritmo Genético leva em conta os custos de partida e as perdas nas usinas hidrelétricas. A metodologia foi aplicada a um caso real do Sistema de usinas Hidrelétricas do rio Paranapanema. Para tornar aplicação amigável foi desenvolvido um programa computacional, o qual integra a metodologia de pré-despacho com uma interface em ambiente windows. Essa interface possibilita a definição da quantidade de usinas que devem operar, a configuração do algoritmo de despacho de máquinas, além da visualização de gráficos e tabelas. O programa foi implementado em linguagem de programação C++, usando a plataforma de programação Builder

Revista de Ciências Gerenciais, Aug 23, 2012

Applied Sciences

The greater flow of containers in global supply chains requires ever-increasing productivity at p... more The greater flow of containers in global supply chains requires ever-increasing productivity at port terminals. The research found in the literature has focused on optimizing specific parts of port operations but has ignored important features, such as the stack-wise organization of containers in a container ship and port yard and the effects of interconnection among the operations in both places. The objective of this paper is to show the importance of designing an integrated plan of the container relocation problem at the port yard with the stowage planning problem for loading and unloading a ship through ports. Both individual problems are NP-Complete, and exact approaches for each problem are only able to find optimal or feasible solutions for small instances. We describe a simulation-optimization methodology that combines simulation, a genetic algorithm, and a new solution representation based on rules. The test results show that the solution from the integrated plan is mutuall...

Avanços em Ciência e Tecnologia de Alimentos - Volume 5, 2021

In a power operation system there are many variables that can influence the execution of the cont... more In a power operation system there are many variables that can influence the execution of the control routines. The attendance of these variables is very important to aid the processes in the safe operation of the system. In the electric system the bus load level is an important variable in the operation planning step. Accurate information on the load level in each bus provide a better control in the power flow, safe and security analysis, operation programming, planning and others. Thus, this work presents two contributions to the bus load forecasting area. The first contribution is the development of a bus load forecast methodology that executes and provides the forecast results for several buses in an aggregate way. The second contribution is a computational system for bus load forecasting named SysPrev-Support System for Bus Load Analysis and Forecasting-developed to facilitate the bus load forecasting process. The aggregate bus load forecasting model is composed by two steps: In the first phase a clustering algorithm is used to identify buses clusters with similar daily load profile and in the second phase is proposed an aggregate structure for to foresee each bus using a conventional prediction model. The SysPrev is a software composed of a data manager subsystem, a model subsystem and a graphical interfaces subsystem. The data manager subsystem is composed of a database that contains bus load time series and other relevant information. The model subsystem is composed of forecasting and clustering techniques. To facilitate the user's interaction, the graphical interface has packages of graphic windows that provide a friendly environment facilitating the integration of the SysPrev and their users. An excellent characteristic of the SysPrev is its construction based on components plug-and-play that allows the insert of new functionalities. With this architecture, each component is produced on an independent way, could be inserted in the software without alterations in the main system. This factor is important, because it supplies the user with the option of customizing and crevii ating new analysis tools, facilitating the updating and the maintenance of the system. The SysPrev was applied to a real power system data composed of 73 buses. The easiness of creating multiple sceneries made possible the fast understanding of the data providing good results in the forecasts, making possible larger precision on the power system operation step.

The Brazilian Power System supplies around 97 % of national energy demand. By reason of the broad... more The Brazilian Power System supplies around 97 % of national energy demand. By reason of the broad Brazilian territory, it requires a transmission system of large scale, due to the large distances between the generations of hydropower and the main concentration of demand that stay in southeastern of Brazil. To ensure security and economy of operation of the Brazilian Electric System are performed analyzes the operation of generation and transmission system due to the conditions of critical loads. The idea is to prepare the system to resist the harshest load conditions. The curve of critical load is calculated for each month with hourly discretization (or less). It's made with the minimum load observed in a given month between the first to eighth hour, and to maximum load observed in the month for the rest of hours. Using the demand agents' history belonging to the Brazilian Power System, it was possible to create a record of five years, 60 months, of curves of critical load. These datas were available by the National Operator of the Brazilian Power System as part of the development of a research project, made available by a decision support system named SysPrev. This dissertation proposed three models to perform the forecasting of the critical load curve. Two models using Artificial Neural Networks and one model using Exponential Smoothing Holt-Winters (HW). The results obtained by all the models were satisfactory and compatible with existing procedures. The exponential smoothing model stood out against the other two models, this having absolute average errors near 3%. These results are justified due to the historical series of curves of critical load has characteristics of trend and seasonality and the HW model is specifically designed for time series with such characteristics.

XXIV Congresso de Iniciação Científica da Unicamp, 2016

Resumo A partir da análise das Cinco Forças de Porter sobre a indústria de bebidas brasileira, é ... more Resumo A partir da análise das Cinco Forças de Porter sobre a indústria de bebidas brasileira, é possível ter um panorama geral e montar uma estratégia para empresas entrantes. Observa-se uma oportunidade de construir uma empresa startup para oferecer a esses entrantes uma solução de eficiência logística para auxiliar e otimizar a decisão de construção de novas plantas de manufatura de bebidas, inicialmente levando em conta os custos logísticos inbound e outbound.

Third International Conference on Natural Computation (ICNC 2007), 2007

ABSTRACT Short-term load forecasting (STLF) has always been a very important issue in power syste... more ABSTRACT Short-term load forecasting (STLF) has always been a very important issue in power system planning and operation. Recently, along with power system privatization and deregulation, accurate forecast of electricity load has received increasing attention. However, forecasting electricity load is difficult because of the randomness and uncertainties of load demand. Support vector machine (SVM) is a novel type of learning machine, which has been successfully employed to solve nonlinear regression and time series problems and showed its potential in STLF. However, the accuracy of STLF is greatly related to the selected parameters of SVM. In this paper, the SCE-UA algorithm, which is an effective and efficient method to optimize model parameters and widely applied to optimize the parameters of the hydrologic models, is employed to optimize the parameters of a SVM model. Subsequently, examples of electricity load data from GuiZhou Power Grid, China were used to compare the forecast performance of the proposed SCE-UA SVM model and back propagation neural network(BPNN) which has obtained wide attention in STLF . The results reveal that the proposed model outperforms the BPNN model. Consequently, the proposed SCE-UA SVM model provides a promising alternative for forecasting electricity load.

Energies

Electric power systems have experienced the rapid insertion of distributed renewable generating s... more Electric power systems have experienced the rapid insertion of distributed renewable generating sources and, as a result, are facing planning and operational challenges as new grid connections are made. The complexity of this management and the degree of uncertainty increase significantly and need to be better estimated. Considering the high volatility of photovoltaic generation and its impacts on agents in the electricity sector, this work proposes a multivariate strategy based on design of experiments (DOE), principal component analysis (PCA), artificial neural networks (ANN) that combines the resulting outputs using Mixture DOE (MDOE) for photovoltaic generation prediction a day ahead. The approach separates the data into seasons of the year and considers multiple climatic variables for each period. Here, the dimensionality reduction of climate variables is performed through PCA. Through DOE, the possibilities of combining prediction parameters, such as those of ANN, were reduced...

2017 IEEE 7th International Conference on Power and Energy Systems (ICPES)

The very short-term bus reactive load forecasting allows the electrical system operator to determ... more The very short-term bus reactive load forecasting allows the electrical system operator to determine the optimal amount of energy to supply the demand with quality, safety and reliability. With this premise, this paper used a knowledge data discovery approach to handle the forecast, from raw data to results analysis, using the neural network for data mining. Two forecasting models were developed: the individual model using only your historical data; and the clustered model using data from other similar buses. The models were applied to Brazilian power system bus data. The results were analyzed according to the error and the confidence level of the forecast.

This paper introduces a new optimization model that integrates the multi-port stowage planning pr... more This paper introduces a new optimization model that integrates the multi-port stowage planning problem with the container relocation problem. This problem is formulated as a binary mathematical programming model that must find the containers' move sequence so that the number of relocations during the whole journey of a ship, as well as the associated port yards is minimized. Modeling by binary variables to represent the cargo status in a ship and yards makes the problem very complex to be solved by exact methods. To the best of our knowledge, this integrated model has not been developed yet as that such problems are always addressed in a partitioned or hierarchical way. A demonstration of the benefits of an integrated approach is given. The model is solved in two different commercial solvers and the results for randomly generated instances are presented and compared to the hierarchical approach. Two heuristics approaches are proposed to quickly generate feasible solutions for warm-starting the model. Extensive computational tests are performed and the results indicate that the solution approaches can reach optimal solutions for small sized instances and good quality solutions on real-scale based instances within reasonable computation time. This is a promising model to support decisions in

Esta tese apresenta um modelo de programacao da operacao de sistemas hidreletricos com restricao ... more Esta tese apresenta um modelo de programacao da operacao de sistemas hidreletricos com restricao de seguranca. A seguranca operacional e um dos aspectos mais importantes na operacao de sistema de energia eletrica, porque a maior parte das faltas no fornecimento de energia eletrica acontece devido a eventos inesperados, como saidas forcadas de equipamentos. A finalidade de um modelo de programacao da operacao de sistemas hidreletricos e definir uma programacao de partidas e paradas das unidades geradoras e os despachos de geracao de energia para os proximos dias. A formulacao matematica do problema resulta em um problema de otimizacao inteira mista nao-linear, que foi tratada por uma abordagem hibrida, combinando o metodo do caminho minimo, o metodo de Newton, a tecnica de conjunto ativo e uma analise de seguranca. O modelo foi aplicado em um estudo de caso baseado no Sistema Interligado Brasileiro. Abstract

Uma das atividades principais na aprendizagem eletronica e o desenvolvimento de conteudo. Este co... more Uma das atividades principais na aprendizagem eletronica e o desenvolvimento de conteudo. Este conteudo pode ser de varios tipos: textos, sons, imagens, animacoes, videos, entre outros. Diante da necessidade de reutilizacao e compartilhamento de informacao na forma de arquivos de diversos tipos por alunos e professores, torna-se relevante investigar novas formas de se aumentar a produtividade durante a autoria ao mesmo tempo em que se busca o favorecimento da aprendizagem. Entre os objetivos pedagogicos do aplicativo desenvolvido, destaca-se o fato deste permitir o trabalho com mapas conceituais, diagramas que buscam favorecer a aprendizagem significativa, a qual guarda forte relacao com criatividade e inovacao, temas de importância na Educacao em Engenharia atual.