Fernando Assis - Academia.edu (original) (raw)

Papers by Fernando Assis

Research paper thumbnail of Lightning-Induced Overvoltage Peaks Considering Soil Parameters Frequency-Dependence: New Approach with Dominant Frequency Associated with Lightning Current Front Time

2022 20th International Conference on Harmonics & Quality of Power (ICHQP)

Research paper thumbnail of Planejamento da Expansão de Sistemas Elétricos de Transmissão via Algoritmo Genético com Estratégias de Diversidade

Procedings do XV Simpósio Brasileiro de Automação Inteligente, 2021

Transmission expansion planning (TEP) is an important study among the various electrical power sy... more Transmission expansion planning (TEP) is an important study among the various electrical power system activities. However, solving the optimization problem resulting from TEP studies for real large electrical systems is a complex task, which involves the analysis of a large space of solutions. In this sense, the present work proposes the investigation of diversity strategies combined with the meta-heuristic Genetic Algorithm (GA) to solve the TEP problem. The Deterministic Crowding and K-means techniques are used to create different versions of GA with population diversity. A real and present-day electrical system, which corresponds to the geoelectric region of southern Brazil, is used to carry out performance studies and analyze the use of different diversity strategies. Resumo: O planejamento da expansão da transmissão (PET) configura um importante estudo dentre as diversas atividades realizadas em um sistema elétrico de potência. No entanto, solucionar o problema de otimização decorrente dos estudos PET para sistemas elétricos reais de grande porteé uma tarefa complexa, que envolve a análise de um grande espaço de soluções. Neste sentido, o presente trabalho propõe a investigação de estratégias de diversidade combinadasà metaheurística Algoritmo Genético (AG) para solução eficiente do problema PET. As técnicas Deterministic Crowding e K-means são utilizadas para criar diferentes versões do AG com diversidade populacional. Um sistema elétrico real e atual, que correspondeà região geoelétrica sul do Brasil,é utilizado para realizar os estudos de desempenho e analisar o emprego de diferentes estratégias de diversidade.

Research paper thumbnail of Planejamento da Expansão de Sistemas de Transmissão via Metaheurística Construtiva

Anais do VI Simpósio Brasileiro de Sistemas Elétricos, 2015

Research paper thumbnail of Reliability evaluation of composite generation and transmission systems via binary logistic regression and parallel processing

International Journal of Electrical Power & Energy Systems

Research paper thumbnail of Author response for "Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

Research paper thumbnail of Planejamento da Transmissão com Critério de Segurança via Algoritmo Genético Aprimorado

This paper proposes the use of an enhanced genetic algorithm model, named AGA-PET, to solve the t... more This paper proposes the use of an enhanced genetic algorithm model, named AGA-PET, to solve the transmission expansion planning problem of electric power system networks. Heuristic information is integrated into the evolutionary process of metaheuristics to improve the expansion plans (solutions), which makes the optimization tool robust and ready to handle different types of systems. This heuristic information is translated in the form of sensitivity indices, based on the circuit loading/ overloading and observed load shedding, considering both the intact network and the “N-1” contingency operating conditions (security criteria). The efficiency of the proposed AGA-PET tool is consistently evaluated through performance statistical indices. Results obtained with systems with different characteristics and dimensions are presented and widely discussed. Resumo: Este artigo propõe o uso de um modelo de algoritmo genético aprimorado, denominado AGAPET na solução do problema do planejament...

Research paper thumbnail of Técnicas Não Supervisionadas de Aprendizado de Máquina Aplicadas na Avaliação da Confiabilidade Composta de Sistemas Elétricos de Potência

This paper proposes a simple and new method for assessing the composite reliability of electrical... more This paper proposes a simple and new method for assessing the composite reliability of electrical power systems. The nonsequential Monte Carlo simulation method is combined with unsupervised machine learning techniques in order to reduce the computational burden involved in the process of estimating composite reliability indices. The proposed approach allows different unsupervised techniques to be employed, in order to obtain significant reductions in processing times, without losing the accuracy of the estimated indices. The results obtained with the use of three different classification techniques (Kohonen self-organizing map, K-means, and K-medoids) are presented and deeply analyzed. Resumo: Neste artigo é proposta uma metodologia simples e nova para avaliação da confiabilidade composta de sistemas elétricos de potência. O método de simulação Monte Carlo não sequencial é combinado com técnicas não supervisionadas de aprendizado de máquina com o intuito de reduzir o esforço comput...

Research paper thumbnail of Previsão de Carga Elétrica para o Horizonte de Curto Prazo via Redes Neurais Artificiais Utilizando C++ e Python

Os avancos tecnologico e social observados atualmente em todo o mundo implicam na exigencia de ni... more Os avancos tecnologico e social observados atualmente em todo o mundo implicam na exigencia de niveis cada vez melhores de eficiencia e de qualidade no fornecimento da energia eletrica. Neste sentido, para garantir a operacao segura e economica dos sistemas eletricos de potencia, o estudo de previsao futura do estado das cargas eletricas desempenha um papel de fundamental importância. Com essa motivacao, nesse trabalho e aplicado um metodo difundido na literatura para previsao diaria de cargas eletricas no horizonte de curto prazo, o metodo Perceptron Multicamadas (MLP), via Algoritmo de Retropropagacao (BP) para treinamento. A implementacao da tecnica de previsao e realizada para avalizacao do desempenho de duas diferentes linguagens de programacao, C++ e Python. A validacao da ferramenta e a analise dos resultados se baseiam na aplicacao de tres diferentes bases de dados, sendo um delas obtida a partir de informacoes atuais disponibilizadas pelo Operador Nacional do Sistema (ONS).

Research paper thumbnail of Planejamento da Manutenção de Unidades Geradoras via Estratégia Evolutiva

This paper proposes a methodology for performing the preventive maintenance scheduling of generat... more This paper proposes a methodology for performing the preventive maintenance scheduling of generating units of an electric power system based on system reliability levels and electricity production costs. Basically, we seek to identify the best time (moment) during the operation to remove electricity generation units for maintenance actions. The metaheuristic Evolution Strategy is used to solve the optimization problems resulting from the proposed methodology employee. To assess the reliability of maintenance schedules during the problem solving process, the Non-Sequential Monte Carlo Simulation algorithm is used. The efficiency of the proposed methodology is illustrated by case studies involving the IEEE-RTS test system, with the scheduling of maintenance of its 32 generation units within a one-year period. The performance of the proposed methodology is evaluated using a statistical performance index, calculated based on the results of different tool runs, with different seeds for p...

Research paper thumbnail of Author response for "Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

Research paper thumbnail of Transmission planning with security criteria via enhanced genetic algorithm

This paper proposes an enhanced genetic algorithm model, named EGA-TEP, to solve the transmission... more This paper proposes an enhanced genetic algorithm model, named EGA-TEP, to solve the transmission expansion planning (TEP) problem of electric power system networks. Heuristic information is integrated into the evolutionary process of metaheuristic to improve the expansion plans (solutions). This heuristic information is translated in the form of sensitivity indices, based on the circuit loading/overloading and observed load shedding, considering both the intact network and the “N-1” contingency operating conditions (security criteria). In addition, an iterative process of evolutionary runs (ERs) is adopted as the basis for designing the EGA-TEP. These contributions make the optimization tool more robust and ready to handle different types of systems. The efficiency of the proposed EGA-TEP tool is consistently evaluated through performance statistical indices. Results obtained with systems with different characteristics and dimensions are presented and widely discussed.

Research paper thumbnail of Well-Being Analysis Applied to the Study of Composite Systems Flexibility Considering Wind Energy Sources

IEEE Latin America Transactions

This paper presents a methodology to evaluate, via well-being analysis, the flexibility of compos... more This paper presents a methodology to evaluate, via well-being analysis, the flexibility of composite electrical systems, considering wind energy sources. By adding wind farms to different system bars, it is possible to assess which configuration provides the best adequacy and safety level for the system. The evaluation is based on probabilistic indices of Loss of Load Expectation (LOLE) and Expected Marginal State (EMS). Such indices are obtained by well-being analysis, combining deterministic criteria with probabilistic methods. Non-Sequential Monte Carlo Simulation is used to consider the probabilistic and intermittent characteristics of wind sources. The methodology is applied to the IEEE-RTS test system.

Research paper thumbnail of Unsupervised machine learning techniques applied to composite reliability assessment of power systems

International Transactions on Electrical Energy Systems

Research paper thumbnail of Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

International Transactions on Electrical Energy Systems

Research paper thumbnail of Generation maintenance scheduling with renewable sources based on production and reliability costs

International Journal of Electrical Power & Energy Systems

Abstract This work proposes an efficient method for solving the generation maintenance scheduling... more Abstract This work proposes an efficient method for solving the generation maintenance scheduling (GMS) problem, defined through an interactive process carried out between the independent system operator (ISO) and generation companies (GENCOs). In this problem, starting from a schedule previously informed by GENCOs, it is desired to minimize the expected costs of production and system load shedding for the period of analysis from the ISO point of view. The Evolution Strategy metaheuristic is used to solve the resulting optimization problem. The non-sequential Monte Carlo simulation and Cross-Entropy methods are combined to efficiently assess the maintenance schedules searched during the solving process. Uncertainties related to the behavior of load, unavailability of generation equipment, and variability of renewable energy sources are taken into account in the modeling and solution of the GMS problem. The performance of the proposed method is tested with the IEEE-RTS modified with the inclusion of renewable sources.

Research paper thumbnail of Planejamento da Manutenção de Unidades Geradoras Mediante Algoritmo Metaheurístico Construtivo

Anais do 14º Simpósio Brasileiro de Automação Inteligente

This paper proposes the use of a constructive metaheuristic algorithm to solve the generating uni... more This paper proposes the use of a constructive metaheuristic algorithm to solve the generating unit maintenance scheduling problem. A reliability based maintenance methodology is considered to provide a quantitative basis for allocation of maintenance efforts and budgets. The proposed tool makes the gradual construction of maintenance plans through local and global search engines, commonly used by optimization techniques. These mechanisms are responsible for ensuring a parsimonious construction process, towards good quality solutions. Sensitivity indices, based on generation system reliability information, are used by the local search engine in the constructive process. The IEEE-RTS system is used for performance analysis of the constructive metaheuristic algorithm, when employed to solve the problem of planning the maintenance of generating units. Resumo: Neste artigo é proposta a utilização de um algoritmo metaheurístico construtivo para solução do problema de planejamento da manutenção de unidades geradoras. Uma metodologia de programação da manutenção baseada em confiabilidade é considerada para fornecer uma base quantitativa para alocação de esforços de manutenção e orçamentos. A ferramenta metaheurística construtiva realiza a construção gradual de planos de manutenção por meio de mecanismos de busca local e de busca global. Esses mecanismos são responsáveis por garantir um processo de construção parcimonioso, que permite a identificação de soluções de boa qualidade para o problema. Índices de sensibilidade, baseados em informações de confiabilidade do sistema de geração, são utilizados pelos mecanismos de busca local durante o processo construtivo. O sistema IEEE-RTS é utilizado para analisar o desempenho do algoritmo metaheurístico construtivo, quando empregado para solução do problema de planejamento da manutenção de unidades geradoras.

Research paper thumbnail of Transmission expansion planning based on relaxed N-1 criteria and reliability indices

2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2016

This paper proposes a new methodology to solve the transmission expansion planning (TEP) problem ... more This paper proposes a new methodology to solve the transmission expansion planning (TEP) problem based on relaxed N-1 criteria. An optimization technique is used to determine the best TEP plans through an adaptive multi-operator evolutionary approach. These plans are obtained by ensuring the N-1 security criterion and also relaxing it to accept pre-specified levels of equipment overload. The major focus is to measure probabilistically the relaxation of TEP plans through traditional reliability indices, and, consequently, the effectiveness of deterministic N-1 based approaches. Discussions are carried out using the results from two test systems: Modified IEEE-RTS and a configuration of the South Brazilian network.

Research paper thumbnail of Optimization of Overhead Transmission Lines Power Transfer Capability with Minimizing Electric and Magnetic Fields

Journal of Control, Automation and Electrical Systems

Research paper thumbnail of Lightning-Induced Overvoltage Peaks Considering Soil Parameters Frequency-Dependence: New Approach with Dominant Frequency Associated with Lightning Current Front Time

2022 20th International Conference on Harmonics & Quality of Power (ICHQP)

Research paper thumbnail of Planejamento da Expansão de Sistemas Elétricos de Transmissão via Algoritmo Genético com Estratégias de Diversidade

Procedings do XV Simpósio Brasileiro de Automação Inteligente, 2021

Transmission expansion planning (TEP) is an important study among the various electrical power sy... more Transmission expansion planning (TEP) is an important study among the various electrical power system activities. However, solving the optimization problem resulting from TEP studies for real large electrical systems is a complex task, which involves the analysis of a large space of solutions. In this sense, the present work proposes the investigation of diversity strategies combined with the meta-heuristic Genetic Algorithm (GA) to solve the TEP problem. The Deterministic Crowding and K-means techniques are used to create different versions of GA with population diversity. A real and present-day electrical system, which corresponds to the geoelectric region of southern Brazil, is used to carry out performance studies and analyze the use of different diversity strategies. Resumo: O planejamento da expansão da transmissão (PET) configura um importante estudo dentre as diversas atividades realizadas em um sistema elétrico de potência. No entanto, solucionar o problema de otimização decorrente dos estudos PET para sistemas elétricos reais de grande porteé uma tarefa complexa, que envolve a análise de um grande espaço de soluções. Neste sentido, o presente trabalho propõe a investigação de estratégias de diversidade combinadasà metaheurística Algoritmo Genético (AG) para solução eficiente do problema PET. As técnicas Deterministic Crowding e K-means são utilizadas para criar diferentes versões do AG com diversidade populacional. Um sistema elétrico real e atual, que correspondeà região geoelétrica sul do Brasil,é utilizado para realizar os estudos de desempenho e analisar o emprego de diferentes estratégias de diversidade.

Research paper thumbnail of Planejamento da Expansão de Sistemas de Transmissão via Metaheurística Construtiva

Anais do VI Simpósio Brasileiro de Sistemas Elétricos, 2015

Research paper thumbnail of Reliability evaluation of composite generation and transmission systems via binary logistic regression and parallel processing

International Journal of Electrical Power & Energy Systems

Research paper thumbnail of Author response for "Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

Research paper thumbnail of Planejamento da Transmissão com Critério de Segurança via Algoritmo Genético Aprimorado

This paper proposes the use of an enhanced genetic algorithm model, named AGA-PET, to solve the t... more This paper proposes the use of an enhanced genetic algorithm model, named AGA-PET, to solve the transmission expansion planning problem of electric power system networks. Heuristic information is integrated into the evolutionary process of metaheuristics to improve the expansion plans (solutions), which makes the optimization tool robust and ready to handle different types of systems. This heuristic information is translated in the form of sensitivity indices, based on the circuit loading/ overloading and observed load shedding, considering both the intact network and the “N-1” contingency operating conditions (security criteria). The efficiency of the proposed AGA-PET tool is consistently evaluated through performance statistical indices. Results obtained with systems with different characteristics and dimensions are presented and widely discussed. Resumo: Este artigo propõe o uso de um modelo de algoritmo genético aprimorado, denominado AGAPET na solução do problema do planejament...

Research paper thumbnail of Técnicas Não Supervisionadas de Aprendizado de Máquina Aplicadas na Avaliação da Confiabilidade Composta de Sistemas Elétricos de Potência

This paper proposes a simple and new method for assessing the composite reliability of electrical... more This paper proposes a simple and new method for assessing the composite reliability of electrical power systems. The nonsequential Monte Carlo simulation method is combined with unsupervised machine learning techniques in order to reduce the computational burden involved in the process of estimating composite reliability indices. The proposed approach allows different unsupervised techniques to be employed, in order to obtain significant reductions in processing times, without losing the accuracy of the estimated indices. The results obtained with the use of three different classification techniques (Kohonen self-organizing map, K-means, and K-medoids) are presented and deeply analyzed. Resumo: Neste artigo é proposta uma metodologia simples e nova para avaliação da confiabilidade composta de sistemas elétricos de potência. O método de simulação Monte Carlo não sequencial é combinado com técnicas não supervisionadas de aprendizado de máquina com o intuito de reduzir o esforço comput...

Research paper thumbnail of Previsão de Carga Elétrica para o Horizonte de Curto Prazo via Redes Neurais Artificiais Utilizando C++ e Python

Os avancos tecnologico e social observados atualmente em todo o mundo implicam na exigencia de ni... more Os avancos tecnologico e social observados atualmente em todo o mundo implicam na exigencia de niveis cada vez melhores de eficiencia e de qualidade no fornecimento da energia eletrica. Neste sentido, para garantir a operacao segura e economica dos sistemas eletricos de potencia, o estudo de previsao futura do estado das cargas eletricas desempenha um papel de fundamental importância. Com essa motivacao, nesse trabalho e aplicado um metodo difundido na literatura para previsao diaria de cargas eletricas no horizonte de curto prazo, o metodo Perceptron Multicamadas (MLP), via Algoritmo de Retropropagacao (BP) para treinamento. A implementacao da tecnica de previsao e realizada para avalizacao do desempenho de duas diferentes linguagens de programacao, C++ e Python. A validacao da ferramenta e a analise dos resultados se baseiam na aplicacao de tres diferentes bases de dados, sendo um delas obtida a partir de informacoes atuais disponibilizadas pelo Operador Nacional do Sistema (ONS).

Research paper thumbnail of Planejamento da Manutenção de Unidades Geradoras via Estratégia Evolutiva

This paper proposes a methodology for performing the preventive maintenance scheduling of generat... more This paper proposes a methodology for performing the preventive maintenance scheduling of generating units of an electric power system based on system reliability levels and electricity production costs. Basically, we seek to identify the best time (moment) during the operation to remove electricity generation units for maintenance actions. The metaheuristic Evolution Strategy is used to solve the optimization problems resulting from the proposed methodology employee. To assess the reliability of maintenance schedules during the problem solving process, the Non-Sequential Monte Carlo Simulation algorithm is used. The efficiency of the proposed methodology is illustrated by case studies involving the IEEE-RTS test system, with the scheduling of maintenance of its 32 generation units within a one-year period. The performance of the proposed methodology is evaluated using a statistical performance index, calculated based on the results of different tool runs, with different seeds for p...

Research paper thumbnail of Author response for "Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

Research paper thumbnail of Transmission planning with security criteria via enhanced genetic algorithm

This paper proposes an enhanced genetic algorithm model, named EGA-TEP, to solve the transmission... more This paper proposes an enhanced genetic algorithm model, named EGA-TEP, to solve the transmission expansion planning (TEP) problem of electric power system networks. Heuristic information is integrated into the evolutionary process of metaheuristic to improve the expansion plans (solutions). This heuristic information is translated in the form of sensitivity indices, based on the circuit loading/overloading and observed load shedding, considering both the intact network and the “N-1” contingency operating conditions (security criteria). In addition, an iterative process of evolutionary runs (ERs) is adopted as the basis for designing the EGA-TEP. These contributions make the optimization tool more robust and ready to handle different types of systems. The efficiency of the proposed EGA-TEP tool is consistently evaluated through performance statistical indices. Results obtained with systems with different characteristics and dimensions are presented and widely discussed.

Research paper thumbnail of Well-Being Analysis Applied to the Study of Composite Systems Flexibility Considering Wind Energy Sources

IEEE Latin America Transactions

This paper presents a methodology to evaluate, via well-being analysis, the flexibility of compos... more This paper presents a methodology to evaluate, via well-being analysis, the flexibility of composite electrical systems, considering wind energy sources. By adding wind farms to different system bars, it is possible to assess which configuration provides the best adequacy and safety level for the system. The evaluation is based on probabilistic indices of Loss of Load Expectation (LOLE) and Expected Marginal State (EMS). Such indices are obtained by well-being analysis, combining deterministic criteria with probabilistic methods. Non-Sequential Monte Carlo Simulation is used to consider the probabilistic and intermittent characteristics of wind sources. The methodology is applied to the IEEE-RTS test system.

Research paper thumbnail of Unsupervised machine learning techniques applied to composite reliability assessment of power systems

International Transactions on Electrical Energy Systems

Research paper thumbnail of Transmission expansion planning of large power networks via constructive metaheuristics with security constraints and load uncertainty analysis

International Transactions on Electrical Energy Systems

Research paper thumbnail of Generation maintenance scheduling with renewable sources based on production and reliability costs

International Journal of Electrical Power & Energy Systems

Abstract This work proposes an efficient method for solving the generation maintenance scheduling... more Abstract This work proposes an efficient method for solving the generation maintenance scheduling (GMS) problem, defined through an interactive process carried out between the independent system operator (ISO) and generation companies (GENCOs). In this problem, starting from a schedule previously informed by GENCOs, it is desired to minimize the expected costs of production and system load shedding for the period of analysis from the ISO point of view. The Evolution Strategy metaheuristic is used to solve the resulting optimization problem. The non-sequential Monte Carlo simulation and Cross-Entropy methods are combined to efficiently assess the maintenance schedules searched during the solving process. Uncertainties related to the behavior of load, unavailability of generation equipment, and variability of renewable energy sources are taken into account in the modeling and solution of the GMS problem. The performance of the proposed method is tested with the IEEE-RTS modified with the inclusion of renewable sources.

Research paper thumbnail of Planejamento da Manutenção de Unidades Geradoras Mediante Algoritmo Metaheurístico Construtivo

Anais do 14º Simpósio Brasileiro de Automação Inteligente

This paper proposes the use of a constructive metaheuristic algorithm to solve the generating uni... more This paper proposes the use of a constructive metaheuristic algorithm to solve the generating unit maintenance scheduling problem. A reliability based maintenance methodology is considered to provide a quantitative basis for allocation of maintenance efforts and budgets. The proposed tool makes the gradual construction of maintenance plans through local and global search engines, commonly used by optimization techniques. These mechanisms are responsible for ensuring a parsimonious construction process, towards good quality solutions. Sensitivity indices, based on generation system reliability information, are used by the local search engine in the constructive process. The IEEE-RTS system is used for performance analysis of the constructive metaheuristic algorithm, when employed to solve the problem of planning the maintenance of generating units. Resumo: Neste artigo é proposta a utilização de um algoritmo metaheurístico construtivo para solução do problema de planejamento da manutenção de unidades geradoras. Uma metodologia de programação da manutenção baseada em confiabilidade é considerada para fornecer uma base quantitativa para alocação de esforços de manutenção e orçamentos. A ferramenta metaheurística construtiva realiza a construção gradual de planos de manutenção por meio de mecanismos de busca local e de busca global. Esses mecanismos são responsáveis por garantir um processo de construção parcimonioso, que permite a identificação de soluções de boa qualidade para o problema. Índices de sensibilidade, baseados em informações de confiabilidade do sistema de geração, são utilizados pelos mecanismos de busca local durante o processo construtivo. O sistema IEEE-RTS é utilizado para analisar o desempenho do algoritmo metaheurístico construtivo, quando empregado para solução do problema de planejamento da manutenção de unidades geradoras.

Research paper thumbnail of Transmission expansion planning based on relaxed N-1 criteria and reliability indices

2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS), 2016

This paper proposes a new methodology to solve the transmission expansion planning (TEP) problem ... more This paper proposes a new methodology to solve the transmission expansion planning (TEP) problem based on relaxed N-1 criteria. An optimization technique is used to determine the best TEP plans through an adaptive multi-operator evolutionary approach. These plans are obtained by ensuring the N-1 security criterion and also relaxing it to accept pre-specified levels of equipment overload. The major focus is to measure probabilistically the relaxation of TEP plans through traditional reliability indices, and, consequently, the effectiveness of deterministic N-1 based approaches. Discussions are carried out using the results from two test systems: Modified IEEE-RTS and a configuration of the South Brazilian network.

Research paper thumbnail of Optimization of Overhead Transmission Lines Power Transfer Capability with Minimizing Electric and Magnetic Fields

Journal of Control, Automation and Electrical Systems