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Master's Dissertation
DOI
https://doi.org/10.11606/D.55.2013.tde-11072013-160623
Document
Author
Full name
Danilo Alvares da Silva
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Carlos, 2013
Supervisor
Committee
Andrade Filho, Marinho Gomes de (President)
Carneiro, Adriano Alber de Franca Mendes
Costa, Eduardo Fontoura
Title in Portuguese
Modelos estocásticos utilizados no planejamento da operação de sistemas hidrotérmicos
Keywords in Portuguese
Inferência bayesiana
Modelo de vazões log-normal truncado
Planejamento ótimo da operação de sistemas hidrotérmicos
Previsão de vazões
Programação dinâmica estocástica
Abstract in Portuguese
Algumas abordagens para o problema de Planejamento Ótimo da Operação de Sistemas Hidrotérmicos (POOSH) utilizam modelos estocásticos para representar as vazões afluentes dos reservatórios do sistema. Essas abordagens utilizam, em geral, técnicas de Programação Dinâmica Estocástica (PDE) para resolver o POOSH. Por outro lado, muitos autores têm defendido o uso dos modelos determinísticos ou, particularmente, a Programação Dinâmica Determinística (PDD) por representar de forma individualizada a interação entre as usinas hidroelétricas do sistema. Nesse contexto, esta dissertação tem por objetivo comparar o desempenho da solução do POOSH obtida via PDD com a solução obtida pela PDE, que emprega um modelo Markoviano periódico, com distribuição condicional Log-Normal Truncada para representar as vazões. Além disso, é realizada a análise com abordagem bayesiana, no modelo de vazões, para estimação dos parâmetros e previsões das vazões afluentes. Comparamos as performances simulando a operação das usinas hidroelétricas de Furnas e Sobradinho, considerando séries de vazões geradas artificialmente
Title in English
Stochastic model used in planning the operation of hydrothermal
Keywords in English
Bayesian inference
Planning optimum the operation of hydrothermal systems
Stochastic dynamic programming
Streamflow forecast
Truncated log-normal streamflow model
Abstract in English
Some approaches for problem of Optimal Operation Planning of Hydrothermal Systems (OOPHS) use stochastic models to represent the inflows in the reservoirs that compose the system. These approaches typically use the Stochastic Dynamic Programming (SDP) to solve the OOPHS. On the other hand, many authors defend the use of deterministic models and, particularly, the Deterministic Dynamic Programming (DDP) since it individually represents the interaction between the hydroelectric plants. In this context, this dissertation aims to compare the performance of the OOPHS solution obtained via DDP with the one given by SDP, which employs a periodic Markovian model with conditional Truncated Log-Normal distribution to represent the inflows. Furthermore, it is performed a bayesian approach analysis, in the inflow model, for estimating the parameters and forecasting the inflows. We have compared the performances of the DDP and SDP solutions by simulating the hydroelectric plants of Furnas and Sobradinho, employing artificially generated series
 
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Danilo_revisada.pdf (2.24 Mbytes)
Publishing Date
2013-07-11
 
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