scholarly journals Application of Marginal Rate of Transformation in Decision Making of Multi-Objective Reservoir Optimal Operation Scheme

2021 ◽  
Vol 13 (3) ◽  
pp. 1488
Author(s):  
Yueqiu Wu ◽  
Liping Wang ◽  
Yanke Zhang ◽  
Jiajie Wu ◽  
Qiumei Ma ◽  
...  
Keyword(s):  
Power Generation ◽  
Decision Making ◽  
Water Level ◽  
Level Scheme ◽  
Flood Control ◽  
Forecast Error ◽  
Optimal Operation ◽  
Total Power ◽  
Marginal Rate ◽  
Multi Objective

For reservoirs with combined storage capacity for flood control and beneficial purposes, there tends to be potential benefit loss when the flood control limited water level is used in medium and small floods. How to find the optimal water level scheme for profit-making and pursue the optimization of comprehensive benefits has always been a difficult problem in multi-objective reservoir optimal operation. Based on the principle of the maximum benefit obtained by the product conversion curve and the isorevenue line in microeconomics, taking flood control and power generation as two products of a reservoir, a multi-objective optimal operation scheme decision-making model is established to seek the highest water level scheme that can produce the maximum comprehensive benefits of flood control and power generation. A case study of the Three Gorges reservoir in the early flood season of a dry year shows that on the one hand, under the condition of deterministic inflow, the model can work out the optimal water level and the corresponding best equilibrium point for both flood control and power generation, and it can increase the total power output by 4.48% without reducing the flood control benefits; on the other hand, it can also obtain the dynamic control area of the maximum allowable water level for power generation considering inflow forecast error, which provides a theoretical reference for determining the starting water level in medium and small floods and utilizing flood resources.

scholarly journals Multi-Objective Joint Optimal Operation of Reservoir System and Analysis of Objectives Competition Mechanism: A Case Study in the Upper Reach of the Yangtze River

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2542 ◽  
Author(s):  
Mufeng Chen ◽  
Zengchuan Dong ◽  
Wenhao Jia ◽  
Xiaokuan Ni ◽  
Hongyi Yao
Keyword(s):  
Power Generation ◽  
Water Supply ◽  
Yangtze River ◽  
Water Resource Management ◽  
Flood Control ◽  
Optimal Operation ◽  
Total Power ◽  
The Yangtze River ◽  
Multi Objective ◽  
Reservoir System

The multi-objective optimal operation and the joint scheduling of giant-scale reservoir systems are of great significance for water resource management; the interactions and mechanisms between the objectives are the key points. Taking the reservoir system composed of 30 reservoirs in the upper reaches of the Yangtze River as the research object, this paper constructs a multi-objective optimal operation model integrating four objectives of power generation, ecology, water supply, and shipping under the constraints of flood control to analyze the inside interaction mechanisms among the objectives. The results are as follows. (1) Compared with single power generation optimization, multi-objective optimization improves the benefits of the system. The total power generation is reduced by only 4.09% at most, but the water supply, ecology, and shipping targets are increased by 98.52%, 35.09%, and 100% at most under different inflow conditions, respectively. (2) The competition between power generation and the other targets is the most obvious; the relationship between water supply and ecology depends on the magnitude of flow required by the control section for both targets, and the restriction effect of the shipping target is limited. (3) Joint operation has greatly increased the overall benefits. Compared with the separate operation of each basin, the benefits of power generation, water supply, ecology, and shipping increased by 5.50%, 45.99%, 98.49%, and 100.00% respectively in the equilibrium scheme. This study provides a widely used method to analyze the multi-objective relationship mechanism, and can be used to guide the actual scheduling rules.

scholarly journals Multi-Objective Optimal Scheduling Model of Dynamic Control of Flood Limit Water Level for Cascade Reservoirs

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1836 ◽  
Author(s):  
Guanjun Liu ◽  
Hui Qin ◽  
Qin Shen ◽  
Rui Tian ◽  
Yongqi Liu
Keyword(s):  
Power Generation ◽  
Water Level ◽  
Flood Control ◽  
Dynamic Control ◽  
Optimal Scheduling ◽  
Cascade Reservoirs ◽  
Multi Objective ◽  
Scheduling Model ◽  
Extreme Risk ◽  
Risk Rate

Reservoirs play a significant role in water resources management and water resource allocation. Traditional flood limited water level (FLWL) of reservoirs is set as a fixed value which over-considers the reservoir flood control and limits the benefits of reservoirs to a certain extent. However, the dynamic control of the reservoir FLWL is an effective solution. It is a method to temporarily increase the water level of the reservoir during the flood season by using forecast information and discharge capacity, and it can both consider flood control and power generation during the flood season. Therefore, this paper focuses on multi-objective optimal scheduling of dynamic control of FLWL for cascade reservoirs based on multi-objective evolutionary algorithm to get the trade-off between flood control and power generation. A multi-objective optimal scheduling model of dynamic control of FLWL for cascade reservoirs which contains a new dynamic control method is developed, and the proposed model consists of an initialization module, a dynamic control programming module and an optimal scheduling module. In order to verify the effectiveness of the model, a cascade reservoir consisting of seven reservoirs in the Hanjiang Basin of China were selected as a case study. Twenty-four-hour runoff data series for three typical hydrological years were used in this model. At the same time, two extreme schemes were chosen for comparison from optimized scheduling schemes. The comparison result showed that the power generation can be increased by 9.17 × 108 kW·h (6.39%) at most, compared to the original design scheduling scheme, while the extreme risk rate also increased from 0.1% to 0.268%. In summary, experimental results show that the multi-objective optimal scheduling model established in this study can provide decision makers with a set of alternative feasible optimized scheduling schemes by considering the two objectives of maximizing power generation and minimizing extreme risk rate.

scholarly journals Optimal Operation of Floodwater Resources Utilization of Lakes in South-to-North Water Transfer Eastern Route Project

2021 ◽  
Vol 13 (9) ◽  
pp. 4857
Author(s):  
Zitong Yang ◽  
Xianfeng Huang ◽  
Jiao Liu ◽  
Guohua Fang
Keyword(s):  
Water Level ◽  
Resource Utilization ◽  
Flood Control ◽  
Optimal Operation ◽  
Water Transfer ◽  
Water Levels ◽  
Reservoir Storage ◽  
Flood Season ◽  
Hongze Lake ◽  
North Water

In order to meet the demand of emergency water supply in the northern region without affecting normal water transfer, considering the use of the existing South-to-North Water Transfer eastern route project to explore the potential of floodwater resource utilization in the flood season of Hongze Lake and Luoma Lake in Jiangsu Province, this paper carried out relevant optimal operating research. First, the hydraulic linkages between the lakes were generalized, then the water resources allocation mode and the scale of existing projects were clarified. After that, the actual available amount of flood resources in the lakes was evaluated. The average annual available floodwater resources in 2003–2017 was 1.49 billion m3, and the maximum available capacity was 30.84 billion m3. Then, using the floodwater resource utilization method of multi period flood limited water levels, the research period was divided into the main flood season (15 July to 15 August) and the later flood season (16 August to 10 September, 11 September to 30 September) by the Systematic Clustering Analysis method. After the flood control calculation, the limited water level of Hongze Lake in the later flood season can be raised from 12.5 m to 13.0 m, and the capacity of reservoir storage can increase to 696 million m3. The limited water level of Luoma Lake can be raised from 22.5 m to 23.0 m (16 August to 10 September), 23.5 m (11 September to 30 September), and the capacity of reservoir storage can increase from 150 to 300 million m3. Finally, establishing the floodwater resource optimization model of the lake group with the goals of maximizing the floodwater transfer amount and minimizing the flood control risk rate, the optimal water allocation scheme is obtained through the optimization algorithm.

A multi-objective risk management model for real-time flood control optimal operation of a parallel reservoir system

2020 ◽  
Vol 590 ◽  
pp. 125264
Author(s):  
Juan Chen ◽  
Ping-an Zhong ◽  
Weifeng Liu ◽  
Xin-Yu Wan ◽  
William W.-G. Yeh
Keyword(s):  
Risk Management ◽  
Real Time ◽  
Flood Control ◽  
Optimal Operation ◽  
Management Model ◽  
Multi Objective ◽  
Reservoir System ◽  
Objective Risk

scholarly journals Short-Term Multi-Objective Optimal Operation of Reservoirs to Maximize the Benefits of Hydropower and Navigation

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1272 ◽  
Author(s):  
Tianlong Jia ◽  
Hui Qin ◽  
Dong Yan ◽  
Zhendong Zhang ◽  
Bin Liu ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Water Level ◽  
Evaluation Method ◽  
Economic Benefits ◽  
Optimal Operation ◽  
Short Term ◽  
Multi Objective ◽  
Capacity Evaluation ◽  
Strength Pareto Evolutionary Algorithm ◽  
Approach Channel

Traditional reservoir operation mainly focuses on economic benefits, while ignoring the impacts on navigation. Thus, the economic operation of reservoirs considering navigational demands is of great significance for improving benefits. A navigation capacity evaluation method (NCEM), which evaluates the navigation capacity considering the influence of flow velocity and water level variation on navigation, is proposed to more effectively evaluate the navigation capacity. Based on two-dimensional hydrodynamic numerical simulation, the NCEM accurately calculates the navigation capacity according to detailed flow velocity and water level changes. In addition, a short-term multi-objective optimal operation model considering the upstream and downstream navigation and power generation is established. Then, the Strength Pareto Evolutionary Algorithm (SPEA2) is used to solve the model. To verify the rationality of the method and model, they are applied to the case study of the Xiangjiaba reservoir. The results demonstrate that the method and model can not only provide a series of operation schemes for decision makers of reservoirs, but also direct the ship to pass safely through the approach channel, implying a certain practical value and significance as a reference for the short-term optimal operation of reservoirs in the future.

scholarly journals Multi-Objective Planning of Distributed Photovoltaic Power Generation Based on Multi-Attribute Decision Making Theory

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223021-223029
Author(s):  
Changchun Cai ◽  
Jie Chen ◽  
Mengrui Xi ◽  
Yuan Tao ◽  
Zhixiang Deng
Keyword(s):  
Power Generation ◽  
Decision Making ◽  
Multi Objective ◽  
Photovoltaic Power ◽  
Multi Attribute Decision Making

scholarly journals Application and comparison of NSGA-II and MOPSO in multi-objective optimization of water resources systems

2018 ◽  
Vol 66 (3) ◽  
pp. 323-329 ◽  
Author(s):  
Ali Hojjati ◽  
Mohsen Monadi ◽  
Alireza Faridhosseini ◽  
Mirali Mohammadi
Keyword(s):  
Water Resources ◽  
Flood Control ◽  
Optimization Methods ◽  
Optimal Operation ◽  
Nsga Ii ◽  
Water Resources Systems ◽  
Multi Objective ◽  
Trade Offs ◽  
Reservoir Systems ◽  
Alternative Solutions

Abstract Optimal operation of reservoir systems is the most important issue in water resources management. It presents a large variety of multi-objective problems that require powerful optimization tools in order to fully characterize the existing trade-offs. Many optimization methods have been applied based on mathematical programming and evolutionary computation (especially heuristic methods) with various degrees of success more recently. This paper presents an implementation and comparison of multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II) for the optimal operation of two reservoirs constructed on Ozan River catchment in order to maximize income from power generation and flood control capacity using MATLAB software. The alternative solutions were based on Pareto dominance. The results demonstrated superior capacity of the NSGA-II to optimize the operation of the reservoir system, and it provides better coverage of the true Pareto front than MOPSO.

Sign in / Sign up

Export Citation Format

Share Document