S-Space College of Engineering/Engineering Practice School (공과대학/대학원) Dept. of Civil & Environmental Engineering (건설환경공학부) Journal Papers (저널논문_건설환경공학부)
Optimizing Operational Policies of a Korean Multireservoir System Using Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction
- Kim, Young-Oh; Eum, Hyung-Il; Lee, Eun-Goo; Ko, Ick Hwan
- Issue Date
- American Society of Civil Engineers
- Journal of Water Resources Planning and Management, 133(1), 4-14
- 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 66.5 m 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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