scholarly journals Modeling and Solving of Joint Flood Control Operation of Large-Scale Reservoirs: A Case Study in the Middle and Upper Yangtze River in China

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 41
Author(s):  
Gang Zha ◽  
Jianzhong Zhou ◽  
Xin Yang ◽  
Wei Fang ◽  
Ling Dai ◽  
...  
Keyword(s):  
Yangtze River ◽  
Flood Control ◽  
Large Scale ◽  
Control Point ◽  
Optimal Operation ◽  
Control Operation ◽  
Upper Yangtze River ◽  
Flood Control Operation ◽  
Flood Diversion

Flood disasters are the most frequent and most severe natural disasters in most countries around the world. Reservoir flood operation is an important method to reduce flood losses. When there are multiple reservoirs and flood control points in the basin, it is difficult to use reservoirs separately to fully realize their flood control potential. However, the multi-reservoir joint flood control operation is a multi-objective, multi-constrained, multi-dimensional, nonlinear, and strong-transition feature decision-making problem, and these characteristics make modeling and solving very difficult. Therefore, a large-scale reservoirs flood control operation modeling method is innovatively proposed, and Dynamic Programming (DP) combined with the Progressive Optimality Algorithm (POA) and Particle Swarm Optimization (PSO) methods, DP-POA-PSO, are designed to efficiently solve the optimal operation model. The middle and upper Yangtze River was chosen as a case study. Six key reservoirs in the basin were considered, including Xiluodu (XLD), Xiangjiaba (XJB), Pubugou (PBG), Tingzikou (TZK), Goupitan (GPT), and Three Gorges (TG). Studies have shown that DP-POA-PSO can effectively solve the optimal operation model. Compared with the current operation method, the joint flood control optimal operation makes the flood control point reach the flood control standard, moreover, in the event of the flood with a return period of 1000 years, Jingjiang, the most critical flood control point of the Yangtze River, does not require flood diversion, and the volume of flood diversion in Chenglingji is also greatly reduced.

scholarly journals Optimal Operation of Cascade Reservoirs for Flood Control of Multiple Areas Downstream: A Case Study in the Upper Yangtze River Basin

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1250 ◽  
Author(s):  
Chao Zhou ◽  
Na Sun ◽  
Lu Chen ◽  
Yi Ding ◽  
Jianzhong Zhou ◽  
...  
Keyword(s):  
Reservoir Operation ◽  
Yangtze River ◽  
Flood Control ◽  
Optimal Operation ◽  
Control Points ◽  
Operation Model ◽  
Cascade Reservoirs ◽  
Upper Yangtze River ◽  
The Upper Yangtze River

The purpose of a flood control reservoir operation is to prevent flood damage downstream of the reservoir and the safety of the reservoir itself. When a single reservoir cannot provide enough storage capacity for certain flood control points downstream, cascade reservoirs should be operated together to protect these areas from flooding. In this study, for efficient use of the reservoir storage, an optimal flood control operation model of cascade reservoirs for certain flood control points downstream was proposed. In the proposed model, the upstream reservoirs with the optimal operation strategy were considered to reduce the inflow of the reservoir downstream. For a large river basin, the flood routing and time-lag cannot be neglected. So, dynamic programming (DP) combined with the progressive optimality algorithm (POA) method, DP-POA, was proposed. Thus, the innovation of this study is to propose a two-stage optimal reservoir operation model with a DP-POA algorithm to solve the problem of optimal co-operation of cascade reservoirs for multiple flood control points downstream during the flood season. The upper Yangtze River was selected as a case study. Three reservoirs from upstream to downstream, Xiluodu, Xiangjiaba and the Three Gorges reservoirs (TGR) in the upper Yangtze River, were taken into account. Results demonstrate that the two-stage optimization algorithm has a good performance in solving the cascade reservoirs optimization problem, because the inflow of reservoir downstream and the division volumes were largely reduced. After the optimal operation of Xiluodu and Xiangjiaba reservoirs, the average reduction of flood peak for all these 13 typical flood hydrographs (TFHs) is 13.6%. Meanwhile, the cascade reservoirs can also store much more storm water during a flood event, and the maximum volumes stored in those two reservoirs upstream in this study can reach 25.2 billion m3 during a flood event. Comprising the proposed method with the current operation method, results demonstrate that the flood diversion volumes at the flood control points along the river decrease significantly.

scholarly journals Joint flood control operation of Upper Yangtze River based on dynamic weight of system safety degree

2018 ◽  
Vol 53 ◽  
pp. 03056
Author(s):  
Zhenghe Li ◽  
Ling Kang ◽  
Liwei Zhou ◽  
Jie Hu
Keyword(s):  
Yangtze River ◽  
Flood Control ◽  
Piecewise Linear ◽  
Design Flood ◽  
System Safety ◽  
Control Operation ◽  
Flood Season ◽  
Dynamic Weight ◽  
Upper Yangtze River ◽  
Flood Control Operation

At flood season, reservoir can guarantee the power generation and other benefit only under the premise of ensuring its own safety and the safety of middle and lower reaches of river basin. For maximizing the comprehensive benefits of each reservoir's function, it is necessary to study the scientific operation strategy of single reservoir and reservoir groups. Joint flood control operation of reservoir groups can achieve the task of flood control to maximum extent and balance the water demands of each reservoir's function. Aimed at five controlling reservoirs in the upper Yangtze river, this paper put forward the static and dynamic weight calculation methods of the system safety degree, and developed a joint flood control operation model of reservoir groups with the goal of minimizing downstream flood volume and maximizing system safety degree of reservoir groups. We studied the flood control effect of two operation strategies, the static weight piecewise linear strategy and the dynamic weight piecewise linear strategy, on downstream flood control station under 100-year design flood condition in 1998. The results showed that the dynamic weight piecewise linear strategy can give full play to the role of each controlling reservoir in flood control operation at flood season.

scholarly journals Risk Assessment and Decision-Making Based on Mean-CVaR-Entropy for Flood Control Operation of Large Scale Reservoirs

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 649 ◽  
Author(s):  
Quansen Wang ◽  
Jianzhong Zhou ◽  
Kangdi Huang ◽  
Ling Dai ◽  
Gang Zha ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Flood Control ◽  
Large Scale ◽  
Yangtze River Basin ◽  
Mean Value ◽  
Operation System ◽  
Control Operation ◽  
Flood Control Operation ◽  
Reservoir Flood Control Operation

The risk inevitably exists in the process of flood control operation and decision-making of reservoir group, due to the hydrologic and hydraulic uncertain factors. In this study different stochastic simulation methods were applied to simulate these uncertainties in multi-reservoir flood control operation, and the risk caused by different uncertainties was evaluated from the mean value, extreme value and discrete degree of reservoir occupied storage capacity under uncertain conditions. In order to solve the conflict between risk assessment indexes and evaluate the comprehensive risk of different reservoirs in flood control operation schemes, the subjective weight and objective weight were used to construct the comprehensive risk assessment index, and the improved Mahalanobis distance TOPSIS method was used to select the optimal flood control operation scheme. The proposed method was applied to the flood control operation system in the mainstream and its tributaries of upper reaches of the Yangtze River basin, and 14 cascade reservoirs were selected as a case study. The results indicate that proposed method can evaluate the risk of multi-reservoir flood control operation from all perspectives and provide a new method for multi-criteria decision-making of reservoir flood control operation, and it breaks the limitation of the traditional risk analysis method which only evaluated by risk rate and cannot evaluate the risk of the multi-reservoir flood control operation system.

scholarly journals Optimal Operation of Complex Flood Control System Composed of Cascade Reservoirs, Navigation-Power Junctions, and Flood Storage Areas

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1883
Author(s):  
Di Zhu ◽  
Yadong Mei ◽  
Xinfa Xu ◽  
Junhong Chen ◽  
Yue Ben
Keyword(s):  
Control System ◽  
Flood Control ◽  
Human Life ◽  
Optimal Operation ◽  
Control Points ◽  
Return Periods ◽  
Control Operation ◽  
Cascade Reservoirs ◽  
Flood Control Operation ◽  
Flood Storage

As more and more water projects are built on rivers, the flood control operation becomes more complex. Studies on the optimal flood control operation are very important to safeguard human life and property. This study focused on optimizing the operation of a complex flood control system composed of cascade reservoirs, navigation-power junctions, flood storage areas, and flood control points. An optimal model was established to jointly maximize flood peak reduction rates of downstream flood control points. A hybrid algorithm named the Dynamic Programming-Progressive Optimality Algorithm (DP-POA) was used to solve this model, and the middle and lower reaches of the Ganjiang River were selected as a case study. The results show that flood reduction at three downstream flood control points ranged from 1080 to 5359 m3/s for designed floods with different return periods, which increased by about 333~1498 m3/s in comparison with the conventional operation. Considering that the maximum water level of reservoirs using DP-POA and the conventional operation is the same, this indicated that DP-POA can make full use of the reservoirs’ flood control storage to reduce downstream flood peaks. In addition, the flood diversion volume of the flood storage area using DP-POA ranged from 0.33 × 108 to 1.79 × 108 m3 for designed floods with 200-year, 300-year, and 500-year return periods, which is smaller than that using the conventional operation.

Towards robust optimization of cascade operation of reservoirs considering streamflow uncertainty

2020 ◽  
Author(s):  
Shaokun He ◽  
Dimitri Solomatine ◽  
Oscar Marquez-Calvo ◽  
Shenglian Guo
Keyword(s):  
Robust Optimization ◽  
River Basin ◽  
Probabilistic Analysis ◽  
Yangtze River ◽  
Flood Control ◽  
Yangtze River Basin ◽  
Control Operation ◽  
Hydropower Production ◽  
Flood Control Operation ◽  
Pareto Fronts

<p><strong>Abstract:</strong> Modern water resource management requires a more robust flood control operation of cascade reservoirs to cope with a more dynamic external environment, whose ultimate goal is to ensure the robust optimization for multiple purposes. To this end, a number of studies with the theme of flood control operation have developed various methods for robust optimization in the presence of uncertainties and in some cases, they may work well. However, these approaches usually incorporate uncertainty into the flood control objectives or constraints and consequently lack explicit robustness indicators that can assist the decision-makers to fully assess the impact of the uncertainty. In order to construct a mature framework of explicit robust optimization of flood control operation, this study uses the Robust Optimization and Probabilistic Analysis of Robustness (ROPAR) technique to identify the robust flood limited water levels of cascade reservoirs for satisfactory compromise hydropower production and flood control risk taking into account the streamflow variability during the flood season: (1) The Monte Carlo method is employed to sample the input set according to the historical streamflow records; (2) The effective non-dominated sorting genetic algorithm II algorithm (NSGA-II) generates a series of Pareto fronts for each hydrograph sample; (3) the ROPAR technique helps building the empirical distribution of the values of hydropower production corresponding to the chosen levels of flood control risk and carry out probabilistic analysis of the Pareto fronts; (4) the ROPAR technique identifies the final robust solutions according to certain criteria. A reservoirs cascade in the Yangtze River basin, China, is considered as a case study. The presented approach allows for studying propagation of uncertainty from the uncertain inflow to the candidate optimal solutions, and selecting the most robust solution, thus better informing decisions related to reservoir operation.</p><p><strong>Key words</strong><strong>：</strong>multi-objective reservoir system, robust optimization, uncertainty, flood control operation, Yangtze River basin</p><p>Reference:</p><p>Marquez-Calvo, O.O., Solomatine, D.P., 2019. Approach to robust multi-objective optimization and probabilistic analysis: the ROPAR algorithm. J Hydroinform, 21(3): 427-440. DOI:10.2166/hydro.2019.095</p>

scholarly journals Joint optimal flood control operation of large scale mixed reservoirs

2018 ◽  
Vol 246 ◽  
pp. 01088
Author(s):  
Gang Zha ◽  
Jianzhong Zhou ◽  
Lu Chen ◽  
Quansen Wang ◽  
Chengwei Lu ◽  
...  
Keyword(s):  
Flood Control ◽  
Large Scale ◽  
Time Lag ◽  
Flood Routing ◽  
Control Points ◽  
Joint Operation ◽  
The Three Gorges ◽  
Upper Yangtze River ◽  
Reservoir Construction

With the reservoir construction gradually completed, joint operation of reservoir groups is an important measure to realize reservoir flood control potential,but when the river basin is large, the flood channel routing and time-lag cannot be simplified, in addition, the curse of dimensionality is very difficult for model solving With the expansion of the number of reservoirs. These factors restrict the application of joint operation of large scale mixed reservoirs.In this study, The DP-POA cyclic iterative algorithm which is based on large scale system decomposed-coordinating method was proposed to solve the optimal problem considering the flood routing and time-lag.The upper Yangtze River is selected as a case study. 6 reservoirs, including the Three Gorges Reservoir(TGR)、Xiangjiaba Reservoir(XJB)、Xiluodu Reservoir (XLD)、 Pubugou Reservoir (PBG)、Goupitan Reservoir (GPT) and Tingzikou Reservoir (TZK)are taken into accounts.Compared with current operation of reservoirs independent,results demonstrate that the method can effectively reduce the maximum operating water level of TGR and flood diversion in the lower reaches of the TGR. Therefore, the safety of the flood control points along the river has been largely improved based on the proposed method.

Adaptive multi-objective simulation–optimization framework for dynamic flood control operation in a river–reservoir system

2015 ◽  
Vol 46 (6) ◽  
pp. 893-911 ◽  
Author(s):  
Om Prakash ◽  
K. Srinivasan ◽  
K. P. Sudheer
Keyword(s):  
Optimization Model ◽  
Flood Control ◽  
Simulation Optimization ◽  
Control Point ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Control Operation ◽  
Multi Objective ◽  
River Reservoir ◽  
Flood Control Operation

An adaptive simulation–optimization (S–O) framework enables dynamic reservoir operational decision-making process during the different phases (time stages) of flood control operation during the passage of a flood event in a river–reservoir system is proposed. This is achieved by incorporating the changing priorities of the reservoir operator/manager at each phase of the flood mitigation operation into the S–O framework by evoking the appropriate set of objective functions and dynamically reconstructing the multi-objective optimization model. Five different objective functions are formulated within the S–O framework, out of which two are concerned with the mitigation at the reservoir; two more deal with the mitigation at the control point; and one ensures sufficient water is stored for meeting future demands. The non-dominated sorting genetic algorithm-II (NSGA-II) is employed to obtain the trade-off solutions from the multi-objective optimization model at each time stage. The results from the study show that the dynamic flood operation model yields a significant level of improvement in flood peak mitigation over the static model both at the reservoir as well as at the control point. The proposed S–O framework can be used in developing either deterministic or probabilistic optimal reservoir release policies for flood control operation, especially where damage functions and penalty functions are not developed.

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