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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... 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.
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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... 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.
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This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution,... more
This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution, bearing in mind investment cost and reliability worth. Reliability worth is considered through the assessment of the interruption costs represented by the index LOLC –
Research Interests: Engineering, Computer Science, Power System, Ant Colony Optimisation, Reliability Engineering, and 12 moreDecision support system, Power System Reliability, Case Study, Metaheuristic, Electric Power System, Decision making process, Ant Colony System, Transmission Expansion Planning, Transportation Network, Indexation, Electrical And Electronic Engineering, and Transmission System
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... 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 Interests:
Research Interests:
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... more
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 computacional envolvido no processo de estimativa dos índices de confiabilidade composta. A metodologia permite que diferentes técnicas não supervisionadas sejam empregadas, tendo em vista a obtenção de reduções significativas nos tempos de processamento, sem que haja perda de precisão dos índices de desempenho estimados. Os resultados obtidos com a utilização de três diferentes técnicas de classificação (Kohonen self-organizing map, K-means, and K-medoids) são apresentados e amplamente analisados.
Research Interests: Physics and Humanities
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... 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...
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Even in a liberalized environment, managing the security of supply associated to the generating system continues to be a major task of the System Operators. The increased use of renewable energy, in particular wind power, adds new... more
Even in a liberalized environment, managing the security of supply associated to the generating system continues to be a major task of the System Operators. The increased use of renewable energy, in particular wind power, adds new challenges to the process, namely in countries like Portugal and Spain, where strong investments in wind power have been done and are foreseen for the next years. In order to tackle this issue, REN (the Portuguese TSO), REE (the Spanish TSO) and INESC Porto (a R&D institute) joined together to develop a project where Monte Carlo simulation is used to evaluate the risk associated with specific future configurations of the generating system, until the horizon of 2025, in the framework of medium and long term generation planning of MIBEL (the Iberian electricity market).
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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... 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.
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Research Interests:
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... 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.
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Research Interests:
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This paper presents a methodology for assessing the reliability indices for composite generation and transmission systems based on Support Vector Machines (SVM). The importance of SVMs is its high generalization ability. The SVMs are used... more
This paper presents a methodology for assessing the reliability indices for composite generation and transmission systems based on Support Vector Machines (SVM). The importance of SVMs is its high generalization ability. The SVMs are used to classify data into two distinct classes. These can be named positive and negative. Thus, the basic idea is to classify the system states into success or failure. For this, a pre-classification of states is achieved by performing the proposed SVM-based neural network, where the sampled states during the beginning of the non-sequential Monte Carlo simulation (MCS) are considered as input data for training and validation sets. By adopting this procedure, a large number of states are classified by a simple evaluation of the network, providing significant reductions in computational costs. The proposed methodology is applied to the IEEE Reliability Test System and to the IEEE Modified Reliability Test System.
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Resumo: Este artigo apresenta uma nova metodologia de análise da confiabilidade preventiva de sistemas de geração. Para avaliar a freqüência de ocorrência dos seguintes estados operativos do sistema: saudável, marginal e de falha, a... more
Resumo: Este artigo apresenta uma nova metodologia de análise da confiabilidade preventiva de sistemas de geração. Para avaliar a freqüência de ocorrência dos seguintes estados operativos do sistema: saudável, marginal e de falha, a metodologia proposta utiliza a simulação Monte Carlo não-seqüencial, um modelo de carga Markoviano não-agregado e um novo processo de estimação de índices de freqüência, denominado transição de estado um passo à frente, o qual é muito flexível e computacionalmente eficiente. Novas funções teste são propostas para a avaliação de índices de confiabilidade preventiva, baseadas neste novo processo de estimação. A metodologia desenvolvida neste trabalho é aplicada ao sistema IEEE-RTS (Reliability Test System) e a uma configuração do sistema SSB (Sul-Sudeste Brasileiro), cujos resultados são apresentados e discutidos. Palavras-chave: Confiabilidade preventiva, Confiabilidade da geração, Simulação Monte Carlo, Modelagem de incertezas.
Heuristic methods have demonstrated the potential to and good feasible solutions, but not necessarily optimal. The success of such methods is related to their ability of avoiding local minima by exploring the basic structure of each... more
Heuristic methods have demonstrated the potential to and good feasible solutions, but not necessarily optimal. The success of such methods is related to their ability of avoiding local minima by exploring the basic structure of each particular problem. These methods can provide high quality solutions, within an acceptable CPU time, even for large-scale problems. This paper presents a new methodology
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Research Interests:
The constant increase in oil prices and the concern over the reduction of gas emissions causing the greenhouse effect favor the creation of policies to encourage the production of energy through renewable sources. The recent restructuring... more
The constant increase in oil prices and the concern over the reduction of gas emissions causing the greenhouse effect favor the creation of policies to encourage the production of energy through renewable sources. The recent restructuring of the electricity sector has introduced new concepts such as power market, transmission open access, cogeneration, independent production, etc., which enabled the decentralized energy generation, strengthening such policies. Thus, non-conventional energy sources, namely wind power, mini-hydro, solar, and cogeneration (e.g., biomass), start having a significant contribution in the energy production matrix. However, if the volatility of the available capacity from such sources is not properly considered, the decisions taken in power systems expansion and/or operation planning can severely endanger the reliability of the power supply. Thus, systems planners and operators will require new computational tools capable of coping with these characteristics, in addition to the recent power system market implementation in a deregulated environment.
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This paper presents a new methodology to evaluating the well-being indices of large composite generation and transmission systems. A well-being framework is used to classify the system states into healthy, marginal and at risk, according... more
This paper presents a new methodology to evaluating the well-being indices of large composite generation and transmission systems. A well-being framework is used to classify the system states into healthy, marginal and at risk, according to a pre-defined deterministic criterion. In order to combine deterministic and probabilistic concepts, the proposed methodology uses a non-sequential Monte Carlo simulation, a multi-level non-aggregate
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This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution,... more
This paper proposes a new methodology to solve transmission expansion planning (TEP) problems in power system, based on the metaheuristic ant colony optimisation (ACO). The TEP problem includes the search for the least cost solution, bearing in mind investment cost and reliability worth. Reliability worth is considered through the assessment of the interruption costs represented by the index LOLC –
Research Interests: Engineering, Computer Science, Power System, Ant Colony Optimisation, Reliability Engineering, and 12 moreDecision support system, Power System Reliability, Case Study, Metaheuristic, Electric Power System, Decision making process, Ant Colony System, Transmission Expansion Planning, Transportation Network, Indexation, Electrical And Electronic Engineering, and Transmission System
9th International Conference on Probabilistic Methods Applied to Power Systems KTH, Stockholm, Sweden - June 11-15, 2006 ... Armando M. Leite da Silva, Fellow, IEEE, Warlley S. Sales, Leonidas C. Resende, Luiz AF Manso, Cleber E.... more
9th International Conference on Probabilistic Methods Applied to Power Systems KTH, Stockholm, Sweden - June 11-15, 2006 ... Armando M. Leite da Silva, Fellow, IEEE, Warlley S. Sales, Leonidas C. Resende, Luiz AF Manso, Cleber E. Sacramento, Leandro S. ...
Research Interests: Computer Science, Economics, Heuristics, Strategic Planning, Investments, and 13 moreMetaheuristics, Uncertainty, Investment, Case Study, Reliability, Costing, Fluctuations, Transmission Expansion Planning, Random Variables, Evolution Strategy, Indexation, Transmission Network, and Transmission Loss
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This paper presents a new methodology for assessing both reliability and well-being indices for composite generation and transmission systems. Firstly, a transmission network reduction is applied to find an equivalent for assessing... more
This paper presents a new methodology for assessing both reliability and well-being indices for composite generation and transmission systems. Firstly, a transmission network reduction is applied to find an equivalent for assessing composite reliability for practical large power systems. After that, in order to classify the operating states, Artificial Neural Networks (ANNs) based on Group Method Data Handling (GMDH) techniques
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ABSTRACT This paper proposes a new approach to evaluate loss of load indices in composite generation and transmission systems. The main idea is to combine a Cross-Entropy (CE)-based optimization process and nonsequential Monte Carlo... more
ABSTRACT This paper proposes a new approach to evaluate loss of load indices in composite generation and transmission systems. The main idea is to combine a Cross-Entropy (CE)-based optimization process and nonsequential Monte Carlo Simulation (MCS) to obtain an auxiliary sampling distribution, which can minimize the variance of the reliability index estimators. This auxiliary sampling distribution will properly modify the original unavailabilities of both generation and transmission equipment, so that important failure events are sampled more often. As a result, the MCS algorithm can reach convergence faster and with fewer samples, leading to significant gains in computational performance, especially when dealing with very reliable system configurations. The proposed method is tested using several composite power systems, including the IEEE RTS 79, IEEE RTS 96, and a configuration of the Brazilian system.
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Research Interests: Computer Science, Power Systems, Monte Carlo Simulation, Monte Carlo Methods, Reliability Engineering, and 9 moreElectric Power System, Data Handling, Reliability Assessment, Artificial Neural Network, Electrical And Electronic Engineering, Monte Carlo Method, Pattern analysis, Monte Carlo Sampling, and Neural nets
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This paper presents an application of Monte Carlo chronological simulation to evaluate the reserve requirements of generating systems, considering renewable energy sources. The idea is to investigate the behavior of reliability indices,... more
This paper presents an application of Monte Carlo chronological simulation to evaluate the reserve requirements of generating systems, considering renewable energy sources. The idea is to investigate the behavior of reliability indices, including those from the well‐being analysis, when the major portion of the energy sources is renewable. Renewable in this work comprises hydroelectric, mini‐hydroelectric, and wind power sources. Case studies on a configuration of the Portuguese Generating System are presented and discussed. Copyright © 2007 John Wiley & Sons, Ltd.