Quantifying the robustness of optimal reservoir operation for the Xinanjiang-Fuchunjiang Reservoir Cascade

2015 ◽  
Vol 16 (1) ◽  
pp. 79-86 ◽  
Author(s):  
E. Vonk ◽  
Y. P. Xu ◽  
M. J. Booij ◽  
D. C. M. Augustijn
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Supply And Demand ◽  
Eastern China ◽  
Nsga Ii ◽  
Reservoir Performance ◽  
Operating Rules ◽  
Operation Rules ◽  
Economic Developments ◽  
The Impact

In this research we investigate the robustness of the common implicit stochastic optimization (ISO) method for dam reoperation. As a case study, we focus on the Xinanjiang-Fuchunjiang reservoir cascade in eastern China, for which adapted operating rules were proposed as a means to reduce the impact of climate change and socio-economic developments. The optimizations were based on five different water supply and demand scenarios for the future period from 2011 to 2040. Main uncertainties in the optimization can be traced back to correctness of the assumed supply and demand scenarios and the quality and tuning of the applied optimization algorithm. To investigate the robustness of proposed operation rules, we (1) compare cross-scenario performance of all obtained Pareto-optimal rulesets and (2) investigate whether different metaheuristic optimization algorithms lead to the same results. For the latter we compare the originally used genetic algorithm (Nondominated Sorting Genetic Algorithm II, NSGA-II) with a particle swarm optimization algorithm (MOPSO). Reservoir performance was measured using the shortage index (SI) and mean annual energy production (MAEP) as main indicators. It is found that optimal operating rules, tailored to a specific scenario, deliver at most 2.4% less hydropower when applied to a different scenario, while the SI increases at most with 0.28. NSGA-II and MOPSO are shown to yield approximately the same Pareto-front for all scenarios, even though small differences can be observed.

scholarly journals Single-reservoir operating rules for a year using multiobjective genetic algorithm

2008 ◽  
Vol 10 (2) ◽  
pp. 163-179 ◽  
Author(s):  
Taesoon Kim ◽  
Jun-Haeng Heo ◽  
Deg-Hyo Bae ◽  
Jin-Hoon Kim
Keyword(s):  
Genetic Algorithm ◽  
Piecewise Linear ◽  
Search Space ◽  
Optimization Method ◽  
Optimal Number ◽  
Current Status ◽  
Nsga Ii ◽  
Multiobjective Genetic Algorithm ◽  
Operating Rules ◽  
Operating Rule

A monthly operating rule for single-reservoir operation is developed in this study. Synthetic inflow data over 100 years are generated by using a time series model, AR(1), and piecewise-linear operating rules consisting of 4 and 5 linear lines are found using the implicit stochastic optimization method. In order to consider multiobjective functions in reservoir system operation, a multiobjective genetic algorithm (NSGA-II) is adopted to obtain the optimization results. The search space of NSGA-II is carefully refined using frequency analysis of historical data, and the relationship between inflow and constraints is also investigated. It is determined that 4 and 5 segments are the optimal number of segments for the piecewise-linear operating rule, and the effect of random number seeding on NSGA-II is evaluated. Six years of historical inflow data are used for the simulation model and the results show that the developed operating rule would handle various inflow series. As a result, probabilistic reservoir storage forecasts can be provided to a system operator so as to enable the operator to evaluate the current status of a reservoir quantitatively.

scholarly journals Impact of Climate Change on Reservoir Reliability: A Case of Bhumibol Dam in Ping River Basin, Thailand

2021 ◽  
Vol 19 (4) ◽  
pp. 266-281
Author(s):  
Allan Sriratana Tabucanon ◽  
◽  
Areeya Rittima ◽  
Detchasit Raveephinit ◽  
Yutthana Phankamolsil ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Demand ◽  
Rainfall Variability ◽  
Wet Season ◽  
Impact Of Climate Change ◽  
Operating Rules ◽  
Operation Rules ◽  
The Future ◽  
Reservoir Release ◽  
The Impact

Bhumibol Dam is the largest dam in the central region of Thailand and it serves as an important water resource. The dam’s operation relies on reservoir operating rules that were developed on the basis of the relationships among rainfall-inflow, water balance, and downstream water demand. However, due to climate change, changing rainfall variability is expected to render the reliability of the rule curves insecure. Therefore, this study investigated the impact of climate change on the reliability of the current reservoir operation rules of Bhumibol Dam. The future scenarios from 2000 to 2099 are based on EC-EARTH under RCP4.5 and RCP8.5 scenarios downscaled by RegCM4. MIKE11 HD was developed for the inflow simulation. The model generates the inflow well (R2=0.70). Generally, the trend of increasing inflow amounts is expected to continue in the dry seasons from 2000-2099, while large fluctuations of inflow are expected to be found in the wet seasons, reflecting high uncertainties. In the case of standard deviations, a larger deviation is predicted under the RCP8.5 scenario. For the reservoir’s operation in a climate change study, standard operating procedures were applied using historical release records to estimate daily reservoir release needed to serve downstream water demand in the future. It can be concluded that there is high risk of current reservoir operating rules towards the operation reliability under RCP4.5 (80% reliability), but the risk is lower under RCP8.5 (87% reliability) due to increased inflow amounts. The unmanageability occurs in the wet season, cautioning the need to redesign the rules.

scholarly journals COVID-19 EXTERNALITIES: ECONOMIC IMPACTS AND POLICY RESPONSES IN CHINA

2021 ◽  
Author(s):  
Olha Posypanko
Keyword(s):  
Quantitative Research ◽  
Supply And Demand ◽  
Chinese Economy ◽  
Future Research ◽  
Policy Responses ◽  
Supply And Demand Shocks ◽  
Global Pandemic ◽  
Chinese Policy ◽  
Economic Developments ◽  
The Impact

This article focuses on the Chinese experience in mitigating the influence of COVID-19 and addresses the impact of the pandemic on the world economy and, in particular, on China`s economy; examines Chinese policy responses to the supply and demand shocks in terms of fiscal and monetary measures, and considers gains and costs of those actions. Thus, the research is made from the stance of China, with regard to its slowdown which concerning economists and may be also aggravated by the trade confrontation. Considering the size of the Chinese economy in terms of global interdependence, its contribution to world growth, and growing weight in the international arena, this study makes timely contributions over determining of the global economic developments and prospects. The result of this study open new avenues for future research and may serve as the source of hypotheses for further quantitative research on Chinese economy and crisis measures amid global pandemic.

A Non-Dominant Sorting Genetic Algorithm for Optimization of a Product Design and Selection of Its Suppliers

2020 ◽  
Vol 19 (01) ◽  
pp. 167-188
Author(s):  
Oulfa Labbi ◽  
Abdeslam Ahmadi ◽  
Latifa Ouzizi ◽  
Mohammed Douimi
Keyword(s):  
Genetic Algorithm ◽  
Product Design ◽  
Computational Time ◽  
Optimization Approach ◽  
Nsga Ii ◽  
Solution Quality ◽  
Holding Costs ◽  
Weighted Sum Method ◽  
The Impact ◽  
Selection Of

The aim of this paper is to address the problem of supplier selection in a context of an integrated product design. Indeed, the product specificities and the suppliers’ constraints are both integrated into product design phase. We consider the case of improving the design of an existing product and study the selection of its suppliers adopting a bi-objective optimization approach. Considering multi-products, multi-suppliers and multi-periods, the mathematical model proposed aims to minimize supplying, transport and holding costs of product components as well as quality rejected items. To solve the bi-objective problem, an evolutionary algorithm namely, non-dominant sorting genetic algorithm (NSGA-II) is employed. The algorithm provides a set of Pareto front solutions optimizing the two objective functions at once. Since parameters values of genetic algorithms have a significant impact on their efficiency, we have proposed to study the impact of each parameter on the fitness functions in order to determine the optimal combination of these parameters. Thus, a number of simulations evaluating the effects of crossover rate, mutation rate and number of generations on Pareto fronts are presented. To evaluate performance of the algorithm, results are compared to those obtained by the weighted sum method through a numerical experiment. According to the computational results, the non-dominant sorting genetic algorithm outperforms the CPLEX MIP solver in both solution quality and computational time.

scholarly journals Le Conseil économique du Canada et le modèle CANDIDE

2009 ◽  
Vol 51 (4) ◽  
pp. 553-567
Author(s):  
J. A. Dawson ◽  
N. E. Wale
Keyword(s):  
Construction Industry ◽  
Supply And Demand ◽  
Energy Investment ◽  
Potential Development ◽  
Economic Forces ◽  
The Subject ◽  
Alternative Scenarios ◽  
Economic Developments ◽  
Special Studies ◽  
The Impact

Abstract The CANDIDE model has been used by the Economic Council to examine Canada's economic potential, to analyze the effects of economic forces, and to consider the appropriateness of alternative policies in reaching economic objectives. For its Annual Reviews, the model provides an analytical basis for taking into account the interdependence of a number of phenomena, including those related to demographic trends, external economic conditions and domestic policies influencing supply and demand, and thus facilitates estimation of the potential development of the economy over the longer term. Within this context, a realizable set of medium-term objectives can then be established. These have been presented by the Council as performance indicators for the three years immediately ahead and they are subsequently used to monitor and assess economic developments. The model also is used by the Council to examine how various economic influences work their way through the Canadian economy. In its Annual Reviews, for example, the effects of alternative scenarios for energy investment and prices have been considered. In a special study of the construction industry, the model was used to trace the causes and effects of instability in this sector. Some illustrative results from each of these impact studies are provided. The model has also been employed to explore the implications of certain past and future changes in commercial policy, including separating out the impact of the Canada-United States Automobile Agreement, and in examining changes that have been taking place in labour markets. Each of these areas have been the subject of special studies carried out by the Council.

A Non-Dominated Sorting Genetic Algorithm Approach for Optimization of Multi-Objective Airport Gate Assignment Problem

2018 ◽  
Vol 2672 (23) ◽  
pp. 59-70 ◽  
Author(s):  
Seyedmirsajad Mokhtarimousavi ◽  
Danial Talebi ◽  
Hamidreza Asgari
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Supply And Demand ◽  
Multiple Criteria Decision Making ◽  
Financial Loss ◽  
Nsga Ii ◽  
Solution Approach ◽  
Multi Objective ◽  
Wide Range ◽  
Gate Assignment

Gate assignment problems (GAP) are one of the most substantial issues in airport operation. The ever-increasing demand producing high occupancy rates of gates, the potential financial loss from imbalances between supply and demand in congested airports, and the limited scope for expanding facilities present challenges that require an advanced methodology for optimal supply allocation. In principle, tackling GAP involves seeking to maintain an airport’s maximum capacity through the best possible allocation of resources (gates). There are a wide range of dependent and independent resources and limitations involved in the problem, adding to the complexity of GAP from both theoretical and practical perspectives. In this study, GAP is extended and mathematically formulated as a three-objective problem, taking into account all resources and restrictions, which can be directly linked to airport authorities’ multiple criteria decision-making processes. The preliminary goal of multi-objective formulation is to consider a wider scope, in which a higher number of objectives are simultaneously optimized, and thus to increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II) as a parallel evolutionary optimization algorithm. Results illustrate that the proposed mathematical model could address most of the major criteria in the decision-making process in airport management in terms of passenger walking distances, robustness, and traditional costs. Moreover, the proposed solution approach shows promise in finding acceptable and plausible solutions compared with other multi-objective algorithms (BAT, PSO, ACO, and ABC).

scholarly journals Research on water resources dispatch model based on improved genetic algorithm – water resources dispatch model

2020 ◽  
Author(s):  
Haoran Fu ◽  
Huahui Li
Keyword(s):  
Genetic Algorithm ◽  
Water Resources ◽  
Water Supply ◽  
Supply And Demand ◽  
Optimal Operation ◽  
Water Withdrawal ◽  
Practical Significance ◽  
Improved Genetic Algorithm ◽  
Reservoir Water ◽  
Operation Rules

Abstract According to the research of reservoir water resources scheduling and distribution, the aim is to balance the water supply and demand in each period, and consider the total water supply and the annual external water withdrawal of the reservoir in each period as water rights. The decision-making variables are provided for the water supply of the reservoir in the paper, so that water demand of the water-receiving area can be better met to alleviate the water shortage at various stages and realize the effective use of water resources. Moreover, through the constraints of reservoir operation rules and other constraints, a mathematical model is established for optimal operation of water resources in the reservoir system. Meanwhile, optimized genetic algorithms are applied to solve the model according to the characteristics of the model. After simulation tests, compared with the traditional linear binary algorithm used in the reservoir, the improved genetic algorithm studied in the paper improves the accuracy of data calculation and data convergence, which proves that the research results of the paper provide theoretical and practical significance for improving the level of reservoir water resources management and solving the problem of optimal water resources scheduling.

scholarly journals Large-scale water scarcity assessment under global changes: insights from a hydroeconomic framework

2016 ◽  
Author(s):  
Noémie Neverre ◽  
Patrice Dumas ◽  
Hypatia Nassopoulos
Keyword(s):  
Water Scarcity ◽  
Large Scale ◽  
Positive Impact ◽  
Supply And Demand ◽  
Global Changes ◽  
Socioeconomic Conditions ◽  
Economic Criterion ◽  
Operating Rules ◽  
Operation Rules ◽  
Trade Offs

Abstract. Global changes are expected to exacerbate water scarcity issues in the Mediterranean region in the next decades. In this work, we investigate the impacts of reservoirs operation rules based on an economic criterion. We examine whether can they help reduce the costs of water scarcity, and whether they become more relevant under future climatic and socioeconomic conditions. We develop an original hydroeconomic model able to compare water supply and demand on a large scale, while representing river basin heterogeneity. On the supply side, we evaluate the impacts of climate change on water inflows to the reservoirs. On the demand side, we focus on the two main sectors of water use: irrigation and domestic sectors. Demands are projected in terms of both quantity and economic value. Coordinated operating rules of the reservoirs are set up, considering spatial and temporal trade-offs. The objective is the maximisation of water benefits. The methodology is applied to Algeria at the 2050 horizon. Our results show that the supply-demand imbalance and its costs will increase in most Algerian basins under future climatic and socioeconomic conditions. Our results suggest that the benefits of operating rules based on economic criteria are not unequivocally increased with global changes. In some basins the positive impact of economic prioritisation is higher in future conditions, but in other basins it is higher in historical conditions. Given its generic nature and low data requirements, the developed framework could be implemented in other regions concerned with water scarcity, or extended to a global coverage.

NSGA-II multi-objectives optimization algorithm for energy management control of hybrid electric vehicle

2018 ◽  
Vol 233 (4) ◽  
pp. 1023-1034 ◽  
Author(s):  
Tao Deng ◽  
Chunsong Lin ◽  
Junlin Luo ◽  
Bingqu Chen
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Optimization Algorithm ◽  
Fuel Economy ◽  
Hybrid Electric Vehicle ◽  
Management Control ◽  
Evaluation Index ◽  
Nsga Ii ◽  
Hybrid Electric ◽  
The Impact

The currently existing energy management control optimization for hybrid electric vehicle (HEV) mainly focuses on fuel economy. Apart from this, there has been some consideration of the impact of emissions, but almost no attention has been paid to drivability performance. Therefore, from the point of view of multi-objectives optimization, the influences of fuel economy, emission and drivability performance on the energy management are comprehensively considered for a parallel HEV. The energy management control parameters and driveline parameters are selected to be optimized parameters. Then, the NSGA-II (Fast Non-dominated Sorting Genetic Algorithm-II) algorithm is proposed to solve the multi-objectives optimization problem. Furthermore, the multi-objectives optimization method for HEV energy management control is established and comparatively simulated with the parallel electric assist control strategy. The results show that the evaluation index of drivability decreases by 27.12% from the maximum and the average enhancement effect of optimization falls by 20.84%. The evaluation index of fuel economy declines by 22.30% from the maximum and the average index drops by 20.26%. The comprehensive index of emission performance descends by 11.33% from the maximum. The proposed multi-objectives optimization algorithm has good convergence and distribution, and obtains more Pareto optimal solution sets, which can provide more selectivity in building HEV energy management control strategies.

scholarly journals Hospital-System Functionality Quantification Based on Supply–Demand Relationship Under Earthquake

2021 ◽  
Author(s):  
Zonghao Hou ◽  
Juan Zhang ◽  
Mingyuan Zhang ◽  
Gang Li
Keyword(s):  
Supply And Demand ◽  
Eastern China ◽  
Medical Resources ◽  
Hospital System ◽  
Damage Prediction ◽  
Medical Supply ◽  
Before And After ◽  
Hospital Systems ◽  
Supply Capacity ◽  
The Impact

Abstract The post-earthquake functionality of hospital systems seriously affects the recovery time of a city, and it is important to quantify the hospital system functionality. This paper presents a method that takes into consideration the post-earthquake medical supply–demand relationship in order to quantify the initial functionality and instantaneous functionality loss of a hospital system under the conditions of an earthquake, which is different from the current quantitative method that takes into consideration only the internal factors of the hospital system. In this method, a geographic information system and an earthquake damage prediction model are first used to obtain the medical supply capacity before and after the earthquake and the medical demand after the earthquake. Based on the results of the post-earthquake medical demand and the distribution of the medical supply capacity, the substitution capacity of medical resources is then calculated. Finally, the substitution capacity of medical resources is used to evaluate the functionality of the hospital system before and after the earthquake. A hospital system of a city in eastern China is considered as an illustrative example, and the impact of changes in the medical supply and demand at different times of the day on the hospital system functionality are analyzed. The results obtained show that the changes in medical supply and demand not only affect the hospital system functionality, but also cause changes in the instantaneous functionality loss of the hospital system after the earthquake. The proposed method can be used to quantify the hospital system functionality and reflect the balance of the medical supply–demand relationship before and after the earthquake, and it can help decision makers in developing a disaster reduction strategy to improve the disaster resilience of the hospital system.

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