Effective Streamflow Process Modeling for Optimal Reservoir Operation Using Stochastic Dual Dynamic Programming
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 4
Abstract
This article presents an innovative streamflow process model for use in reservoir operational rule design in stochastic dual dynamic programming (SDDP). Model features, which can be applied independently, are (1) a multiplicative process model for the forward phase and its linearized version for the backward phase; and (2) a nonuniform time-step length that is inversely proportional to seasonal variability. The advantages are (1) guaranteeing positive streamflow values still maintaining problem linearity, and (2) making system adaptation faster during high variable periods. Model identification is straightforward, as with the additive periodic autoregressive model generally used in SDDP. The proposed model is applied on the Senegal River system for the optimal operation of Manantali Reservoir and evaluated against the streamflow process model currently used in the water management literature.
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Acknowledgments
Luciano Raso’s research was funded by the AXA Research Fund.
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Journal of Water Resources Planning and Management
Volume 143 • Issue 4 • April 2017
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©2017 American Society of Civil Engineers.
History
Received: Apr 12, 2016
Accepted: Oct 5, 2016
Published online: Jan 30, 2017
Published in print: Apr 1, 2017
Discussion open until: Jun 30, 2017
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