A platform for research: civil engineering, architecture and urbanism
Dynamic Control of Flood Limited Water Levels for Parallel Reservoirs by Considering Forecast Period Uncertainty
The objective of this study is to achieve the dynamic optimization of the flood limited water level (FLWL) in parallel reservoirs, using Luhun Reservoir and Guxian Reservoir as case studies. The innovation lies in establishing a dynamic control optimization model for the FLWL of parallel reservoirs, considering the uncertainty in the forecasting period of the flood forecast due to the varying locations of the rainstorm center from upstream to downstream. To commence, the Fisher optimal segmentation method is employed for flood season staging to determine the staged FLWL of each reservoir. Subsequently, considering the uncertainty in the foresight period, the upper range of the dynamic FLWL is determined through the improved pre-discharge capacity constraint method and Monte Carlo simulation. Finally, a multi-objective optimization model is established to determine the optimal dynamic FLWL control operation scheme for parallel reservoirs, utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This model takes into account both downstream flood control requirements and the water supply benefits of the parallel reservoirs. Through the optimization of the scheme, the water supply of the parallel reservoirs can be augmented by 15,347.6 m3 during the flood season. This optimization effectively achieves a harmonious balance between flood control and water supply, holding significant implications for mitigating drought risks amid changing conditions.
Dynamic Control of Flood Limited Water Levels for Parallel Reservoirs by Considering Forecast Period Uncertainty
The objective of this study is to achieve the dynamic optimization of the flood limited water level (FLWL) in parallel reservoirs, using Luhun Reservoir and Guxian Reservoir as case studies. The innovation lies in establishing a dynamic control optimization model for the FLWL of parallel reservoirs, considering the uncertainty in the forecasting period of the flood forecast due to the varying locations of the rainstorm center from upstream to downstream. To commence, the Fisher optimal segmentation method is employed for flood season staging to determine the staged FLWL of each reservoir. Subsequently, considering the uncertainty in the foresight period, the upper range of the dynamic FLWL is determined through the improved pre-discharge capacity constraint method and Monte Carlo simulation. Finally, a multi-objective optimization model is established to determine the optimal dynamic FLWL control operation scheme for parallel reservoirs, utilizing the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). This model takes into account both downstream flood control requirements and the water supply benefits of the parallel reservoirs. Through the optimization of the scheme, the water supply of the parallel reservoirs can be augmented by 15,347.6 m3 during the flood season. This optimization effectively achieves a harmonious balance between flood control and water supply, holding significant implications for mitigating drought risks amid changing conditions.
Dynamic Control of Flood Limited Water Levels for Parallel Reservoirs by Considering Forecast Period Uncertainty
Yanbin Li (author) / Yubo Li (author) / Kai Feng (author) / Kaiyuan Tian (author) / Tongxuan Huang (author)
2023
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Many-Objective Hierarchical Pre-Release Flood Operation Rule Considering Forecast Uncertainty
DOAJ | 2024
|Flood Mitigation through Joint Flood Control of Parallel Reservoirs
British Library Conference Proceedings | 1995
|Water Balance in Irrigation Reservoirs Considering Flood Control and Irrigation Efficiency Variation
British Library Online Contents | 2016
|Flood Storage Allocation Rules for Parallel Reservoirs
British Library Conference Proceedings | 2014
|Flood Storage Allocation Rules for Parallel Reservoirs
Online Contents | 2015
|