scholarly journals A New Multi-Objective Optimization Model of Water Resources Considering Fairness and Water Shortage Risk

Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2648
Author(s):  
Xiaoyu Tang ◽  
Ying He ◽  
Peng Qi ◽  
Zehua Chang ◽  
Ming Jiang ◽  
...  
Keyword(s):  
Water Resources ◽  
Optimization Model ◽  
Optimal Allocation ◽  
Risk Index ◽  
Water Shortage ◽  
Economic Benefits ◽  
Selection Strategy ◽  
Multi Objective Optimization ◽  
Structural Water ◽  
Multi Objective

Assessing the fairness of water resource allocation and structural water shortage risks is an urgent problem that needs to be solved for the optimal allocation of water resources. In this study, we established a new multi-objective optimization model of water resources based on structural water shortage risks and fairness. We propose an improved NSGA-III based on the reference point selection strategy (ARNSGA-III) to solve the optimization model. The superiority of this method was proven by comparing it with three other methods, namely, NSGA-III, MOSPO, and MOEA/D. The model was applied to optimize the allocation of water resources in Wusu City in China. The results show that the new multi-objective optimization model provides reasonable and feasible solutions for solving water conflicts. The convergence and stability of ARNSGA-III are better than those of the other three algorithms. Allocation schemes of water resources for Wusu City in normal years, dry years, and extremely dry years are proposed. In normal years, the structural water shortage risk index is reduced by 50.1%, economic benefits increased by 0.2%, and fairness is reduced by 60.5%. This study can provide new ideas for solving the multi-objective optimization of regional water resources.

The Multi-Objective Optimization Allocation Model of Water Resources in Xiaokai River Irrigation Area

2015 ◽  
Vol 1092-1093 ◽  
pp. 1289-1294
Author(s):  
Xin Wang ◽  
Jing Xu ◽  
Ke Kong ◽  
Lei Yan ◽  
Fang Wu
Keyword(s):  
Water Resources ◽  
Optimization Model ◽  
Supply And Demand ◽  
Reference Value ◽  
Multi Objective Optimization ◽  
Allocation Model ◽  
Irrigation Area ◽  
Multi Objective ◽  
Groundwater Environment ◽  
Sequence Method

For the three big problems of water resources supply and demand contradiction, protection of groundwater environment and sediment over long distances in Xiaokai river irrigation area, the model of water utilization benefit maximization, groundwater level optimal control and the goal of sediment transport effect optimization model are established, and coupled into a multi-objective optimization model. The model is solved by using The delaminating sequence method, obtained the rational allocation plan of water resources in water years, and analyzing the rationality of the plan. The results show that, the scheme comprehensively considers the economic and environmental issues and has great reference value to promote sustainable development of irrigation area.

scholarly journals Analysis and Research on the Optimal Allocation of Regional Water Resources

2018 ◽  
Vol 38 ◽  
pp. 03055
Author(s):  
Xi rui-chao ◽  
Gu yu-jie
Keyword(s):  
Water Resources ◽  
Basic Concept ◽  
Optimal Allocation ◽  
Present Situation ◽  
Water Shortage ◽  
Social Benefits ◽  
Allocation Model ◽  
Multi Objective ◽  
Optimal Allocation Model ◽  
Regional Water

Starting from the basic concept of optimal allocation of water resources, taking the allocation of water resources in Tianjin as an example, the present situation of water resources in Tianjin is analyzed, and the multi-objective optimal allocation model of water resources is used to optimize the allocation of water resources. We use LINGO to solve the model, get the optimal allocation plan that meets the economic and social benefits, and put forward relevant policies and regulations, so as to provide theoretical which is basis for alleviating and solving the problem of water shortage.

An Multi-Objective Optimization Model for Wind-Storage Combined Operation

2013 ◽  
Vol 860-863 ◽  
pp. 414-418
Author(s):  
Yan Qing Li ◽  
Hao Shan Li ◽  
Chi Dong ◽  
Jian Wang
Keyword(s):  
Wind Power ◽  
Optimization Model ◽  
Large Scale ◽  
Wind Farm ◽  
Economic Benefits ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Wind Power Integration ◽  
Optimization Calculation ◽  
Combined Operation

Large-scale wind power integration constituted great challenges for the power system operation and dispatching, due to the volatile and peak-reversal nature of wind power.The multi-objective optimization model of the wind farm combined with pumped-storage was studied to solve the problem.An optimization model for wind-storage combined operation was established, aiming at tracking load changes ,improving wind power economic benefits and peak shaving benefits, using improved multi-objective particle swarm optimization.The optimization calculation attempted to reduce volatility of the remaining load after removal of wind-storage joint output and increase economic benefits of wind farrms. Through the optimization calculation the wind farm and storage plant scheduling values of each time are available. The calculation example shows that the model and method are conducive to large-scale wind power integration and have a certain practicality and effectiveness.

scholarly journals A multi-objective water trading optimization model for Henan Province's water-receiving area in the Middle Route of China's South-to-North Water Diversion Project

Water Policy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 693-707
Author(s):  
M. Dou ◽  
J. Zhang ◽  
G. Li ◽  
P. Zhao
Keyword(s):  
Optimization Model ◽  
Water Shortage ◽  
Economic Benefits ◽  
Henan Province ◽  
Water Diversion ◽  
Optimal Scheme ◽  
Multi Objective ◽  
Water Trading ◽  
Water Diversion Project ◽  
North Water

Abstract Water trading is an effective method for solving regional water shortage problems and addressing the uneven spatiotemporal distribution of water resources. Therefore, taking the Middle Route of China's South-to-North Water Diversion Project (MR-SNWDP) as the research object, we present a study on a feasible water trading scheme in the water-receiving area of Henan Province. First, the tradable water of each calculation unit in the water-receiving area was calculated by analyzing the water-saving potential of different industries. Second, a multi-objective optimization model for trading water between different regions was developed, taking the largest social and economic benefits of the water-receiving area as the objective function. Finally, non-dominated sorting genetic algorithms were used to solve this optimization model, and an optimal scheme for water trading was proposed. The simulated results of the optimal scheme indicate that the total water shortage of the water-receiving areas will decrease by 650.69 million m3, and there will be a surplus of 14.98 million m3 of water, and the gross national product will increase by RMB 130.5 billion at a rate of 5.2%. This demonstrates that the water-receiving areas of Henan Province can effectively alleviate local water shortages by trading water without increasing external water supplies.

scholarly journals Multi-Objective Optimization for Reservoir Operation Considering Water Diversion and Power Generation Objectives

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1540 ◽  
Author(s):  
Xiaomei Sun ◽  
Jungang Luo ◽  
Jiancang Xie
Keyword(s):  
Power Generation ◽  
Water Resources ◽  
Reservoir Operation ◽  
Weight Vector ◽  
Water Shortage ◽  
Water Diversion ◽  
Volume Index ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Adaptive Weight

Due to the uneven distribution of water resources in time and space, the problem of water shortage has become increasingly serious in some areas. To optimize use of water resources, it is urgent to establish multi-objective models and apply effective optimization algorithms to guide reservoir management. This study proposed a model of multi-objective optimization for reservoir operation (MORO) with the objectives of maximizing water diversion and power generation. The multi-objective evolutionary algorithm based on decomposition with adaptive weight vector adjustment (MOEA/D-AWA) was applied to solve the MORO problem. In addition, the performance of the MOEA/D-AWA was compared with two other algorithms based on the hyper-volume index. Huangjinxia reservoir, which is located in Shaanxi, China, was selected as the case study. The results show that: (1) the proposed model is effective and reasonable in theory; (2) the optimization results obtained by MOEA/D-AWA demonstrate this algorithm can be applied to the MORO problem, providing a set of evenly distributed non-dominated solutions; and (3) water diversion and power generation are indeed contradictory objectives. The MORO strategy can be used to efficiently utilize water resources, improve the comprehensive benefits of reservoirs, and provide decision support for actual reservoir operation.

scholarly journals Application of an Interval Two-Stage Robust (ITSR) Optimization Model for Optimization of Water Resource Distribution in the Yinma River Basin, Jilin Province, China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2910
Author(s):  
Wei He ◽  
Luze Yang ◽  
Minghao Li ◽  
Chong Meng ◽  
Yu Li
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Use ◽  
Water Resource ◽  
Low Income ◽  
Optimization Model ◽  
Resource Distribution ◽  
Water Shortage ◽  
Economic Benefits ◽  
Two Stage

The present study is based on the application of an interval two-stage stochastic programming (ITSP) model in the Yinma River Basin. A robust method based on interval two-stage robust (ITSR) optimization is introduced to construct an optimization model of water resource distribution in order to solve the problems of water shortage in low-income and high-income areas caused by the unreasonable distribution of water resources. The model would help in reducing the system risk in the Yinma River Basin caused by an excessive pursuit of economic benefits. The model simulations show that the amount of water required for the water resource distribution is significantly reduced after balancing the risks and the water resource distribution of the water use departments is reduced by up to 20%. In addition, the situation of water scarcity of various water use departments shows a decreasing trend. There is no scarcity of water use in Panshi, Yongji, Shuangyang and Jiutai areas. The water shortage of water use departments in other areas is reduced by up to 97%. The allocation of reused water to ecological and environmental departments with higher water demand further solved the water shortage problem in low-income departments in the interval-two-stage planning model. In this study, after the introduction of the robust optimization method in the Yinma River Basin, the stability of the water resources distribution system is significantly improved. In addition, the risk of water use system in the interval-two-stage stochastic model can be avoided.

scholarly journals Application of AMOGWO in Multi-Objective Optimal Allocation of Water Resources in Handan, China

Water ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 63
Author(s):  
Su Li ◽  
Zhihong Yan ◽  
Jinxia Sha ◽  
Jing Gao ◽  
Bingqing Han ◽  
...  
Keyword(s):  
Water Resources ◽  
Optimal Allocation ◽  
Convergence Rates ◽  
High Reliability ◽  
Water Shortage ◽  
Gray Wolf ◽  
Total Water ◽  
Multi Objective ◽  
Comparison Results ◽  
Gray Wolf Optimizer

The reasonable allocation of water resources using different optimization technologies has received extensive attention. However, not all optimization algorithms are suitable for solving this problem because of its complexity. In this study, we applied an ameliorative multi-objective gray wolf optimizer (AMOGWO) to the problem. For AMOGWO, which is based on the multi-objective gray wolf optimizer, we improved the distance control parameter calculation method, added crowding degree for the archive, and optimized the selection mechanism for leader wolves. Subsequently, AMOGWO was used to solve the multi-objective optimal allocation of water resources in Handan, China, for 2035, with the maximum economic benefit and minimum social water shortage used as objective functions. The optimal results obtained indicate a total water demand in Handan of 2740.43 × 106 m3, total water distribution of 2442.23 × 106 m3, and water shortage of 298.20 × 106 m3, which is consistent with the principles of water resource utilization in Handan. Furthermore, comparison results indicate that AMOGWO has substantially enhanced convergence rates and precision compared to the non-dominated sorting genetic algorithm II and the multi-objective particle swarm optimization algorithm, demonstrating relatively high reliability and applicability. This study thus provides a new method for solving the multi-objective optimal allocation of water resources.

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

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