en The application of mathematical optimization techniques to reservoir system operation, besides allowing a more rational use of water, can also help to justify allocation decisions and solve conflicts. However, this application is not a simple task since it must deal with the inherent uncertainties, nonlinearities and multiobjectivity of the hydrosystems (Rani and Moreira 2009). In the literature, reservoir systems operation optimization is often modelled as a multistage stochastic programming problem and solved with a Stochastic Dynamic Programming (SDP) algorithm. However, the application of SDP is limited to systems with few reservoirs due to its curse of dimensionality. Pereira and Pinto (1991) developed the Stochastic Dual Dynamic Programming (SDDP), an extension of SDP that attenuates the curse of dimensionality by avoiding the variables discretization. The SDDP was first developed for the optimization of large hydropower generation systems (Pereira and Pinto 1991; Scott and Read 1996; Mo et al. 2001) and today its application to multipurpose reservoir systems is becoming more usual (Tilmant et al. 2008; Marques and Tilmant 2013; Raso et al. 2017). The present work seeks to apply and evaluate the performance of the SDDP algorithm in the optimization of the joint operation of two multipurpose reservoir systems. The hydrossystem chosen for this study is the Jaguaribe-Metropolitano wich supplies water for most of the Ceará state (Brazil). The hydrosystem is composed by the Jaguaribe and Metropolitan basins reservoir systems. Jaguaribe comprises the greatest reservoirs of the State, presenting a predominant demand for …
%0 Journal Article
%1 porto2019application
%A Porto, VC
%A Filho, FA Souza
%A Carvalho, TMN
%A Rocha, RV
%A Frota, RL
%D 2019
%K imported topic_earthenvironment
%T Application of stochastic dual dynamic programming in operation optimization of the Jaguaribe-Metropolitano reservoirs system
%X en The application of mathematical optimization techniques to reservoir system operation, besides allowing a more rational use of water, can also help to justify allocation decisions and solve conflicts. However, this application is not a simple task since it must deal with the inherent uncertainties, nonlinearities and multiobjectivity of the hydrosystems (Rani and Moreira 2009). In the literature, reservoir systems operation optimization is often modelled as a multistage stochastic programming problem and solved with a Stochastic Dynamic Programming (SDP) algorithm. However, the application of SDP is limited to systems with few reservoirs due to its curse of dimensionality. Pereira and Pinto (1991) developed the Stochastic Dual Dynamic Programming (SDDP), an extension of SDP that attenuates the curse of dimensionality by avoiding the variables discretization. The SDDP was first developed for the optimization of large hydropower generation systems (Pereira and Pinto 1991; Scott and Read 1996; Mo et al. 2001) and today its application to multipurpose reservoir systems is becoming more usual (Tilmant et al. 2008; Marques and Tilmant 2013; Raso et al. 2017). The present work seeks to apply and evaluate the performance of the SDDP algorithm in the optimization of the joint operation of two multipurpose reservoir systems. The hydrossystem chosen for this study is the Jaguaribe-Metropolitano wich supplies water for most of the Ceará state (Brazil). The hydrosystem is composed by the Jaguaribe and Metropolitan basins reservoir systems. Jaguaribe comprises the greatest reservoirs of the State, presenting a predominant demand for …
@article{porto2019application,
abstract = {[en] The application of mathematical optimization techniques to reservoir system operation, besides allowing a more rational use of water, can also help to justify allocation decisions and solve conflicts. However, this application is not a simple task since it must deal with the inherent uncertainties, nonlinearities and multiobjectivity of the hydrosystems (Rani and Moreira 2009). In the literature, reservoir systems operation optimization is often modelled as a multistage stochastic programming problem and solved with a Stochastic Dynamic Programming (SDP) algorithm. However, the application of SDP is limited to systems with few reservoirs due to its curse of dimensionality. Pereira and Pinto (1991) developed the Stochastic Dual Dynamic Programming (SDDP), an extension of SDP that attenuates the curse of dimensionality by avoiding the variables discretization. The SDDP was first developed for the optimization of large hydropower generation systems (Pereira and Pinto 1991; Scott and Read 1996; Mo et al. 2001) and today its application to multipurpose reservoir systems is becoming more usual (Tilmant et al. 2008; Marques and Tilmant 2013; Raso et al. 2017). The present work seeks to apply and evaluate the performance of the SDDP algorithm in the optimization of the joint operation of two multipurpose reservoir systems. The hydrossystem chosen for this study is the Jaguaribe-Metropolitano wich supplies water for most of the Ceará state (Brazil). The hydrosystem is composed by the Jaguaribe and Metropolitan basins reservoir systems. Jaguaribe comprises the greatest reservoirs of the State, presenting a predominant demand for …},
added-at = {2024-11-29T11:56:28.000+0100},
author = {Porto, VC and Filho, FA Souza and Carvalho, TMN and Rocha, RV and Frota, RL},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/24c36ac06310cb0dff5734197a3c835d1/joum576e},
citation = {11th World Congress on Water Resources and Environment: Managing Water …, 2019},
interhash = {5b4eb4ba5839a6a020bd3e909ddc04f4},
intrahash = {4c36ac06310cb0dff5734197a3c835d1},
keywords = {imported topic_earthenvironment},
timestamp = {2024-11-29T11:56:28.000+0100},
title = {Application of stochastic dual dynamic programming in operation optimization of the Jaguaribe-Metropolitano reservoirs system},
year = 2019
}
