Stable Improved Dynamic Programming Method: An Efficient and Accurate Method for Optimization of Reservoir Flood Control Operation

The optimal algorithm to ensure computational efficiency and accuracy remains to be challenging for the development of robust operation model to solve the optimization problem of reservoir operation, particularly for applications involving flood control with complex flood hydrograph. The dynamic pro...

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Vydáno v:Water resources management Ročník 37; číslo 14; s. 5635 - 5654
Hlavní autoři: Chai, Fuxin, Peng, Feng, Zhang, Hongping, Zang, Wenbin
Médium: Journal Article
Jazyk:angličtina
Vydáno: Dordrecht Springer Netherlands 01.11.2023
Springer Nature B.V
Témata:
Accuracy
Algorithms
Atmospheric Sciences
case studies
Civil Engineering
Computer applications
Convergence
Dynamic programming
Earth and Environmental Science
Earth Sciences
Environment
Flood control
Flood hydrographs
Floods
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
hydrograph
Hydrology/Water Resources
Optimization
prediction
Relaxation method (mathematics)
Reservoir operation
system optimization
water
Stable improved dynamic programming
Curse of dimensionality
Flood control
Reservoir operation optimization
ISSN:0920-4741, 1573-1650
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Shrnutí:The optimal algorithm to ensure computational efficiency and accuracy remains to be challenging for the development of robust operation model to solve the optimization problem of reservoir operation, particularly for applications involving flood control with complex flood hydrograph. The dynamic programming (DP) is one of the most popular methods to solve optimization problem, but it is limited the “curse of dimensionality” problem. The improved dynamic programming (IDP) method has been proposed to overcome this defeat of DP, remaining the convergence problem. The relaxation method based on approximate monotonic relationship shows potential to ensure convergence of IDP. In this study, the theoretical search range of the relaxation method are analyzed. A stable improved dynamic programming (SIDP) method is proposed based on relaxation method and a prediction method of schedulable storage states. The proposed SIDP overcomes the complex computational problem of DP and the convergence problem of IDP. The case study on an ideal reservoir and the Guanting reservoir, shows that SIDP can achieve an accuracy as high as DP, but with a much higher efficiency than DP. This method shows a strong solution to optimization problems of reservoir flood control operation.
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-023-03622-w