Optimizing Operational Policies of a Korean Multireservoir System Using Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction
Publication: Journal of Water Resources Planning and Management
Volume 133, Issue 1
Abstract
This study presents state-of-the-art optimization techniques for enhancing reservoir operations which use sampling stochastic dynamic programming (SSDP) with ensemble streamflow prediction (ESP). SSDP used with historical inflow scenarios (SSDP/Hist) derives an off-line optimal operating policy through a backward-moving solution procedure. In contrast, SSDP used with monthly forecasts of ESP (SSSDP/ESP) reoptimizes the off-line policy. These stochastic models are used to derive a monthly joint operating policy during the drawdown period of the Geum River multireservoir system in Korea. A cross-validation test of 1,900 simulation runs demonstrates that: (1) proposed stochastic models that explicitly include inflow uncertainty are superior to those that do not; (2) updating policy with ESP forecasts is appropriate in this reservoir system; (3) the lower dam of the Geum River multireservoir system should maintain elevation of during the beginning of the drawdown period to avoid significant increase in the downstream water shortages; and (4) forecasting accuracy may result in considerable effects on joint reservoir operations.
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Acknowledgments
This research was supported by a grant (Code No. UNSPECIFIED1-6-1) from Sustainable Water Resources Research Center of 21st Century Frontier Research Program and also by the Engineering Research Institute, Seoul National University, Seoul, Korea. The writers wish to express their gratitude to Professor Jery Stedinger of Cornell University, Dr. Myung-Ky Park and Mr. Ji-Hyun Yun of KOWACO, and reviewers for their constructive comments.
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Information
Published In
Journal of Water Resources Planning and Management
Volume 133 • Issue 1 • January 2007
Pages: 4 - 14
Copyright
© 2007 ASCE.
History
Received: Mar 11, 2005
Accepted: Sep 22, 2005
Published online: Jan 1, 2007
Published in print: Jan 2007
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