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THE INFLUENCE OF THE FORECAST MODEL ERROR ON OPTIMIZING THE STORAGE FUNCTION CONTROL OF THE RESERVOIR USING
Abstract
One of the ways to manage drought is to use optimization when managing the storage function of reservoirs. Optimizing reservoir management itself requires inflow forecasts. A lot of forecasting models have been created in the world, which according to many authors can be used for the given purpose. The models themselves are generally assessed according to classical criteria. The article therefore attempts to determine whether the quality of the forecast model for the mentioned application can be assessed as a whole (the model must be able to predict the entire interval of occurrence of flows) or whether the local quality of the model is sufficient (the model can predict a defined interval of occurrence of flows with good quality). For this purpose, a fictitious forecasting model was built that makes predictions based on real flow series and white noise. The predictions created in this way are then used to control the real reservoir using the deterministic evolution method. The achieved results are then compared with the results when a directly real series was used for control. The results themselves may be somewhat surprising, as certain combinations of the fictitious model predictions achieved better results than the results obtained using the real values according to the chosen criterion.
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Kotaska, S., Riha, J., Zeman, E.,Fisher, M., Trnka, M., Concept of water management solution of selected reservoirs from the general LAPV in the Dyje basin for assessment of adaptation measures against the effects of climate, conference proceeding Vodni nadrze 2022, Brno, Povodi Moravy,s.p.,ISBN 978-80-907141-6-8, 2022.
Hirsch, R., Synthetic Hydrology and Water Supply Reliability. Water Resources Research - WATER RESOUR RES. 15. 1603-1615. DOI: 10.1029/WR015i006p01603., 1979
Kozel, T., Stary, M., Adaptive Stochastic Management of the Storage Function for a Large, Open Reservoir Using Learned Fuzzy Models. Journal of Hydrology and Hydromechanics 70, no. 2 213�21, 2022. DOI: 10.2478/johh-2022-0010
Cheng, C. T., Feng, Z.-K., Niu, W.-J., and Liao, S.-L., Heuristic Methods for Reservoir Monthly Inflow Forecasting: A Case Study of Xinfengjiang Reservoir in Pearl River, China, Water, 7, 4477�4495, DOI: 10.3390/w7084477 2015.
Luo, X., Yuan, X., Zhu, S., Xu, Z., Meng, L., and Peng, J., A hybrid support vector regression framework for streamflow forecast, J. Hydrol., 568, 184�193, DOI: 10.1016/j.jhydrol.2018.10.064 2019.
Iman, R., Latin Hypercube Sampling. DOI: 10.1002/9780470061596.risk0299, 1999.
Price, K., Storn, R., Lampinen, J., Differential evolution: A practical approach to global optimization, Berlin: Springer-Verlag, 2005.
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