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The thesis presents a method of committing generating units in a hydro-thermal power system within practical computer resources such as computer time and data storage.

Orientador: Secundino Soares Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-06T08:33:44Z (GMT). No. of bitstreams: 1 PastorHumpiri_CarolinaJanet_M.pdf: 2093723 bytes, checksum: 2ef978811ccdca91867a3a47544e6581 (MD5) Previous issue date: 2005 / Resumo: O objetivo do Planejamento Energético da Operação de sistemas hidrotérmicos de geração é encontrar uma política operativa que forneça energia elétrica ao sistema, em um determinado período de planejamento, com confiabilidade e por um custo mínimo. Isto equivale a determinar um cronograma ótimo de geração para cada usina, a cada intervalo, de modo que o sistema atenda a demanda de forma confiável. Este trabalho faz uso de um dos paradigmas da Computação Evolutiva, as Estratégias Evolutivas (EEs), cuja característica principal é a auto-adaptação dos seus parâmetros durante o processo evolutivo, para a solução do problema de planejamento energético da operação. É feita uma comparação entre as abordagens por EEs e por Programação Não Linear baseada em Fluxo em Redes, para usinas do Sistema Elétrico Brasileiro. As EEs mostraram-se boas ferramentas para apurar a solução fornecida pela programação não linear devido ao elevado poder de exploração do espaço de soluções / Abstract: The objective of the energetic operation planning of hydrothermal generation systems is to find an operation policy that supplies electric energy to the system, during a given planning period, with reliability and by a minimum cost. This is equivalent determining an optimal scheduling of generation for each plant, at each interval, in such a way that the system load is attained with reliability. This work make use of one of the paradigms of Evolutionary Computation, Evolution Strategies (ES), whose main characteristic is the self-adaptation of its parameters during the evolution process, for the solution of the energetic operation planning. A comparison is performed for hydro plants of the Brazilian power system between the ES and the nonlinear network flow approaches. The ES approach turns to be a good tool to improve the solution obtained by the nonlinear programming approach due to its high potential to explore and exploit the solution space / Mestrado / Energia Eletrica / Mestre em Engenharia Elétrica

Orientador: Secundino Soares Filho / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-15T02:32:47Z (GMT). No. of bitstreams: 1 Zambelli_MonicadeSouza_D.pdf: 4122152 bytes, checksum: 3256b0546520645ef065b43111b44374 (MD5) Previous issue date: 2009 / Resumo: O planejamento da operação energética do Sistema Interligado Nacional (SIN) é uma tarefa complexa realizada por meio de uma cadeia de modelos de médio, curto e curtíssimo prazo acoplados entre si, cada um com considerações pertinentes à etapa que aborda. A proposta deste trabalho é apresentar uma alternativa para o planejamento da operação energética de médio prazo. Foi desenvolvida uma metodologia baseada em modelo de controle preditivo, abordando os aspectos estocásticos do problema de forma implícita pela utilização de valores esperados das vazões, e fazendo uso de um modelo determinístico de otimização a usinas individualizadas, que possibilita uma representação mais precisa do sistema hidrotérmico. A análise de desempenho é feita através de simulações da operação, considerando os parques hidrelétrico e termelétrico que compõem o SIN, com restrições operativas reais, em configuração dinâmica, com plano de expansão e a possibilidade de intercâmbio e importação de mercados vizinhos. Os resultados são comparados aos fornecidos pela metodologia em vigor no setor elétrico brasileiro, notadamente o modelo NEWAVE, que determina as decisões de geração por subsistema, e o modelo Suishi-O, que as desagrega por usinas individualizadas / Abstract: The long term hydrothermal scheduling of the Brazilian Integrated System (SIN) is a complex task solved by a chain of long, medium and short term coupled models, each one with considerations pertinent to the stage of operation that it deals with. The proposal of this work is to present an alternative for the long term hydrothermal scheduling. A methodology based on model predictive control was developed, implicitly handling stochastic aspects of the problem by the use of inflows expected values, and making use of a deterministic optimization model to obtain the optimal dispatch for individualized plants, what makes possible a more accurate representation of the hydrothermal system. The performance analysis is made through simulations of the operation, taking into consideration all the hydro and thermal plants that compose the SIN, with real operative constraints, in dynamic configuration, with its expansion plan and the possibility of interchange and importation from neighboring markets. The results are compared with those provided by the approach actually in use by the Brazilian electric sector, specifically the NEWAVE model, which defines the generation decisions for the subsystems, and the Suishi-O model, that disaggregates them for the individualized plants / Doutorado / Energia Eletrica / Doutor em Engenharia Elétrica

The main objective of this thesis is to investigate risk neutral and risk averse approaches to multistage stochastic programming with applications to hydrothermal operation planning problems. The purpose of hydrothermal system operation planning is to define an operation strategy which, for each stage of the planning period, given the system state at the beginning of the stage, produces generation targets for each plant. This problem can be formulated as a large scale multistage stochastic linear programming problem. The energy rationing that took place in Brazil in the period 2001/2002 raised the question of whether a policy that is based on a criterion of minimizing the expected cost (i.e. risk neutral approach) is a valid one when it comes to meet the day-to-day supply requirements and taking into account severe weather conditions that may occur. The risk averse methodology provides a suitable framework to remedy these deficiencies. This thesis attempts to provide a better understanding of the risk averse methodology from the practice perspective and suggests further possible alternatives using robust optimization techniques. The questions investigated and the contributions of this thesis are as follows. First, we suggest a multiplicative autoregressive time series model for the energy inflows that can be embedded into the optimization problem that we investigate. Then, computational aspects related to the stochastic dual dynamic programming (SDDP) algorithm are discussed. We investigate the stopping criteria of the algorithm and provide a framework for assessing the quality of the policy. The SDDP method works reasonably well when the number of state variables is relatively small while the number of stages can be large. However, as the number of state variables increases the convergence of the SDDP algorithm can become very slow. Afterwards, performance improvement techniques of the algorithm are discussed. We suggest a subroutine to eliminate the redundant cutting planes in the future cost functions description which allows a considerable speed up factor. Also, a design using high performance computing techniques is discussed. Moreover, an analysis of the obtained policy is outlined with focus on specific aspects of the long term operation planning problem. In the risk neutral framework, extreme events can occur and might cause considerable social costs. These costs can translate into blackouts or forced rationing similarly to what happened in 2001/2002 crisis. Finally, issues related to variability of the SAA problems and sensitivity to initial conditions are studied. No significant variability of the SAA problems is observed. Second, we analyze the risk averse approach and its application to the hydrothermal operation planning problem. A review of the methodology is suggested and a generic description of the SDDP method for coherent risk measures is presented. A detailed study of the risk averse policy is outlined for the hydrothermal operation planning problem using different risk measures. The adaptive risk averse approach is discussed under two different perspectives: one through the mean-$avr$ and the other through the mean-upper-semideviation risk measures. Computational aspects for the hydrothermal system operation planning problem of the Brazilian interconnected power system are discussed and the contributions of the risk averse methodology when compared to the risk neutral approach are presented. We have seen that the risk averse approach ensures a reduction in the high quantile values of the individual stage costs. This protection comes with an increase of the average policy value - the price of risk aversion. Furthermore, both of the risk averse approaches come with practically no extra computational effort and, similarly to the risk neutral method, there was no significant variability of the SAA problems. Finally, a methodology that combines robust and stochastic programming approaches is investigated. In many situations, such as the operation planning problem, the involved uncertain parameters can be naturally divided into two groups, for one group the robust approach makes sense while for the other the stochastic programming approach is more appropriate. The basic ideas are discussed in the multistage setting and a formulation with the corresponding dynamic programming equations is presented. A variant of the SDDP algorithm for solving this class of problems is suggested. The contributions of this methodology are illustrated with computational experiments of the hydrothermal operation planning problem and a comparison with the risk neutral and risk averse approaches is presented. The worst-case-expectation approach constructs a policy that is less sensitive to unexpected demand increase with a reasonable loss on average when compared to the risk neutral method. Also, we comp are the suggested method with a risk averse approach based on coherent risk measures. On the one hand, the idea behind the risk averse method is to allow a trade off between loss on average and immunity against unexpected extreme scenarios. On the other hand, the worst-case-expectation approach consists in a trade off between a loss on average and immunity against unanticipated demand increase. In some sense, there is a certain equivalence between the policies constructed using each of these methods.

Orientadores: Sergio Valdir Bajay, Paulo Sergio Franco Barbosa / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-08T23:23:08Z (GMT). No. of bitstreams: 1 Pereira_AndreFlavioSoares_M.pdf: 1792951 bytes, checksum: a865e5b33783ba4a8f044bcff70f9809 (MD5) Previous issue date: 2006 / Resumo: Nesta dissertação se avalia o estado da arte do planejamento da operação energética e da manutenção de usinas em sistemas hidrotérmicos de potência e se propõe algumas inovações. Neste contexto, se faz uma revisão crítica das metodologias de planejamento empregadas no setor elétrico brasileiro, incluindo as bases de dados que dão suporte a estas metodologias e dando destaque às práticas atuais do Operador Nacional do Sistema Elétrico (ONS); várias propostas de avanços metodológicos são feitas ao longo desta parte do trabalho. Uma outra parte desta dissertação envolve a aplicação de um modelo de otimização, a médio prazo, da operação de algumas usinas do Sistema Interligado Nacional (SIN), pertencentes a uma concessionária geradora no Estado de São Paulo, satisfazendo as metas de geração impostas pelo planejamento centralizado do SIN, realizado pelo ONS, e restrições associadas ao uso múltiplo da água nos reservatórios destas usinas, dentre outras. Várias funções-objetivo podem ser utilizadas neste modelo, dependendo das finalidades a serem atingidas nas simulações. O modelo foi aplicado ao parque gerador hidrelétrico da empresa AES, nos rios Tietê e Pardo; algumas simulações foram feitas, discutindo-se os resultados alcançados / Abstract: The state-of-the-art of power plant scheduling and maintenance planning in hydro-thermal power systems is evaluated in this thesis and some innovations are proposed. In this context, a critical review of the planning methodologies employed in the Brazilian power sector is carried out, including the data bases which support these methodologies and pointing out the current practices of the National Operator of the Power System (ONS); several proposals concerning advances in these methodologies are put forward along this work. In another part of this thesis, the medium-term scheduling of some power stations of the National Interlinked System (SIN) belonging to a utility in the State of São Paulo are modeled through an optimization algorithm, which meets the generation targets imposed by the centralized planning of SIN, carried out by ONS, and constraints associated to multiple uses of water in the reservoirs of these plants, among other constraints. Several objective functions can be used in this model, depending on the purposes to be achieved in the simulations. The model was applied to the hydroelectric generation system of the company AES, in the rivers Tietê and Pardo; some simulations were carried out and their results are discussed in the thesis / Mestrado / Planejamento de Sistemas Energeticos / Mestre em Planejamento de Sistemas Energéticos