Long-Term Stochastic Reservoir Operation Using a Noisy Genetic Algorithm

To deal with stochastic characteristics of inflow in reservoir operation, a noisy genetic algorithm (NGA), based on simple genetic algorithms (GAs), is proposed. Using operation of a single reservoir as an example, the results of NGA and Monte Carlo method which is another way to optimize stochastic reservoir operation were compared. It was found that the noisy GA was a better alternative than Monte Carlo method for stochastic reservoir operation.     

隔河岩水库入库径流随机模拟研究

根据实测日流量过程资料分析清江流域的洪水统计特征和自相关结构,分别用AR模型和典型解集模型进行随机模拟,并对模拟结果进行分析与检验,经研究认为典型解集模型对隔河岩水库入库径流模拟效果相对较好。     

A Novel Solution for Stochastic Dynamic Game of Water Allocation from a Reservoir Using Collocation Method

In this study, a continuous model of stochastic dynamic game for water allocation from a reservoir system was developed. The continuous random variable of inflow in the state transition function was replaced with a discrete approximant rather than using the mean of the random variable as is done in a continuous model of deterministic dynamic game. As a result, a new solution method was used to solve the stochastic model of game based on collocation method. The collocation method was introduced as an alternative to linear-quadratic (LQ) approximation methods to resolve a dynamic model of game. The collocation method is not limited to the first and second degree approximations, compared to LQ approximation, i.e. Ricatti equations. Furthermore, in spite of LQ related problems, consideration of the stochastic nature of game on the action variables in the collocation method would be possible. The proposed solution method was applied to the real case of reservoir operation, which typically requires considering the effect of uncertainty on decision variables. The results of the solution of the stochastic model of game are compared with the results of a deterministic solution of game, a classical stochastic dynamic programming model (e.g. Bayesian Stochastic Dynamic Programming model, BSDP), and a discrete stochastic dynamic game model (PSDNG). By comparing the results of alternative methods, it is shown that the proposed solution method of stochastic dynamic game is quite capable of providing appropriate reservoir operating policies.     

Robust Methods for Identifying Optimal Reservoir Operation Strategies Using Deterministic and Stochastic Formulations

Water allocation in a competing environment is a major social and economic challenge especially in water stressed semi-arid regions. In developing countries the end users are represented by the water sectors in most parts and conflict over water is resolved at the agency level. In this paper, two reservoir operation optimization models for water allocation to different users are presented. The objective functions of both models are based on the Nash Bargaining Theory which can incorporate the utility functions of the water users and the stakeholders as well as their relative authorities on the water allocation process. The first model is called GA–KNN (Genetic Algorithm–K Nearest Neighborhood) optimization model. In this model, in order to expedite the convergence process of GA, a KNN scheme for estimating initial solutions is used. Also KNN is utilized to develop the operating rules in each month based on the derived optimization results. The second model is called the Bayesian Stochastic GA (BSGA) optimization model. This model considers the joint probability distribution of inflow and its forecast to the reservoir. In this way, the intrinsic and forecast uncertainties of inflow to the reservoir are incorporated. In order to test the proposed models, they are applied to the Satarkhan reservoir system in the north-western part of Iran. The models have unique features in incorporating uncertainties, facilitating the convergence process of GA, and handling finer state variable discretization and utilizing reliability based utility functions for water user sectors. They are compared with the alternative models. Comparisons show the significant value of the proposed models in reservoir operation and supplying the demands of different water users.     

Stochastic Simulation of Daily Suspended Sediment Concentration Using Multivariate Copulas

An estimation of daily suspended sediment concentration (SSC) is required for water resource and environmental management. The traditional methods for simulating daily SSC focus on modeling the SSCs themselves, whereas the cross-correlation structure between SSC and streamflow has received only minor attention. To address this issue, we propose a stochastic method to generate long-term daily SSC using multivariate copula functions that account for temporal and cross dependences in daily SSCs. We use the conditional copula method to construct daily multivariate distributions to alleviate the complications and workload of parameter estimations using high-dimensional copulas. The observed daily streamflow and SSC data are normalized using the normal quantile transform method to relax the computationally intensive model of building daily marginal distributions. Daily SSCs can thus be simulated through the multivariate conditional distribution using previous daily SSC and concurrent daily streamflow values. The proposed method is rigorously examined by application to a case study at the Pingshan station in the Jinsha River Basin, China, and compared with the bivariate copula method. The results show that the proposed method has a high degree of accuracy, in preserving the statistics and temporal correlation of daily SSC observations, and better preserves the lag-0 cross correlation compared with the bivariate copula method. The multivariate copula framework proposed here can accurately and efficiently generate long-term daily SSC data for water resource and environmental management, which play a critical role in accurately estimating the frequency and magnitude of extreme SSC events.

     

处理好水库移民监理中的几个关系

结合黄河小浪底水库移民监理的实践，阐述了在水库移民监理中应处理好移民监理单位与业主，移民监理单位与实施机构，移民监理单位与设计单位，移民监理单位与移民，移民监理单位内部之间的几个关系。认为只有处理好移民监理单位与业主，实施机构，设计单位，移民之间的关系，相互配合，才能顺利地实现移民监理中的“进度控制，质量控制，投资控制，合同管理，信息管理和组织协调”，从而充分发挥监理的作用。     

Inventory Theory-Based Stochastic Optimization for Reservoir Water Allocation

Water Resources Management - This study aims to develop an effective model for reservoir water allocation under conditions of uncertainty. To identify a practical method that increases the benefits...     

利用NAM模型对松华坝水库入库径流的模拟研究

通过对松华坝水库入库径流的模拟介绍NAM模型使用的基本步骤,对不同参数模拟结果进行对比.发现Umax、Lmax、CQOF对径流总量影响明显,CK1、CK2对峰值的影响明显.建议先确定Umax和CQOF中的某一个然后调整另外一个,参数调整时可首先对这个几个参数进行校准.     

Reliability Improved Stochastic Dynamic Programming for Reservoir Operation Optimization

Stochastic Dynamic Programming (SDP) is widely used in reservoir operation problems. Besides its advantages, a few drawbacks have leaded many studies to improve its structure. Handling the infeasible conditions and curse of dimensionality are two major challenges in this method. The main goal of this paper is proposing a new method to avoid infeasible conditions and enhance the solution efficiency with new discretization procedure. For this purpose, an optimization module is incorporated into regular SDP structure, so that, near optimal values of state variables are determined based on the available constraints. The new method (RISDP) employs reliability concept to maximize the reservoir releases to satisfy the downstream demands. Applying the proposed technique improves the reservoir operating policies compared to regular SDP policies with the same assumptions of discretization. Simulation of reservoir operation in a real case study indicates about 15% improvement in objective function value and elimination of infeasible conditions by using RISDP operating policies.     

Feasibility Improved Stochastic Dynamic Programming for Optimization of Reservoir Operation

Water Resources Management - Stochastic Dynamic Programming (SDP) is a major method for optimizing reservoir operation. Handling non-linear, non-convex and non-differentiable objective functions...     

渔洞水库入库月径流过程的随机模拟

本文以实测４２年径流资料为基础，分别采用季节性ＡＲ（１）、季节性ＡＲ（２）、季节性ＡＲ（３）、季节性ＡＲ（１）－ＡＲ（２）混合和季节性ＡＲ（１）－ＡＲ（２）＿ＡＲ（３）混合模型对渔洞水库径流过程进行随机模拟，得出１００个样本，最后通过对所得径流样本中种参数的统计分析，推荐出最佳模型。     

暴雨洪水流域系统随机模拟（研究之二）

暴雨洪水流域系统的输入,本文首次成功地引用具有明显优点的正则展开模型随机模拟暴雨过程;流域系统的输送,采用了简便可行的产、汇流模型;各子模型及系统输出的洪水过程检验表明,流域系统随机模拟的效果是令人满意的。     

Ex Ante Impact Assessment of Reservoir Construction Projects for Different Stakeholders Using Agent-Based Modeling

Reservoir construction projects are frequently met with fierce opposition. Consequently, to mitigate any potential negative impacts, environmental and social impact assessments are usually mandatory. Stakeholder perspectives are often only implicit in such assessments, and the medium-term effects of mitigating actions are assessed at the aggregate level, which fails to take into account unequal disaggregated impacts. In this paper, we design and apply an agent-based model (ABM) built on stakeholder information to conduct an ex ante assessment of the impact of a reservoir construction project in southern Thailand over a 30-year period for individual agents. We incorporate stakeholders’ knowledge into the ABM on the basis of primary data collected during the 2016–2018 period, including workshops with affected farmers to assess their interests and concerns, in-depth interviews with farmers in nearby districts to assess farming behaviors, and the expert opinions of policymakers to assess the relevant regulations and processes. In a case study for which the model was established, the results predict that, overall, farmers will have more farm income if the dam is built. We find that affected people require a standard of living similar to that provided by their previous livelihood as soon as possible after resettlement. By simulating the impacts on individual agents, we conclude that the compensation for relocation offered to affected farmers is not sufficient for sustainable resettlements. Facilitating compensation may increase the speed of project implementation and lead to better outcomes for everyone, including affected communities, whereas failure to reshape the current compensation policy leaves everyone more disadvantaged.

     

小浪底水库水环境质量预测模拟研究

小浪底大坝建成运行后 ,水库库区的水力特性及水质特性将发生变化。根据三门峡大坝至小浪底大坝间河段的水文水质特性 ,建立了两坝间水力、水质模型 ,并据此对工程投入运行后库区水流、水质特性的变化进行预测     

Soil Water Simulation and Predication Using Stochastic Models Based on LS-SVM for Red Soil Region of China

The seasonal drought and the low available soil moisture affect the agricultural production in red soil region, China. Therefore, it is necessary to simulate and predict the dynamic changes of soil water in the field. Presently, dynamic model has been applied to obtain the soil water information. While the simulation accuracy of dynamic model depends on many complicated parameters, which are difficult to obtain. In this study, the various nonlinear Stochastic Model of soil water simulation systems and chaotic time series analysis methods of prediction systems had been set up. In the nonlinear Stochastic Model of soil water simulation systems, the daily soil water content simulated by Least squares support vector machine (LS-SVM) with the meteorological factors had more stabilities and advantages in soil water simulation performance over the Back Propagation Artificial Neural Network (BP-ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). In chaotic time series analysis method of prediction systems, the various signal preprocessing methods including the appropriate de-noising methods and wavelet decomposition methods were applied to preprocess the original chaotic soil water signal. The results of the prediction systems showed that the appropriate de-noising methods and the tendency of wavelet transformation had less effect on the delay time (τ) and embedding dimension (m). The de-noising methods may ignore the detail information of the soil water signal, while the appropriate wavelet transformation to get smaller Maximum Lyapunov Exponent (λ₁) of the chaotic soil water signal detail and tendency information can improve the predicting capacity.     

水库调度中隐式与显式随机优化方法的对比

以二滩水电站水库为例,介绍、搭建了隐式与显式随机水库优化调度模型;利用二滩电站的历史径流序列,针对2种随机模型,分别进行了模拟优化调度;对比分析了隐式随机与显式随机的调度结果,得出2种方法的优缺点,并为下一步研究奠定了基础.     

Development of a New Simulation Model for the Reservoir Hydropower Generation

Hydroelectric power development plans are of great importance in today’s world, due to the urgency of access to clean energy resources. Hydroelectric power plants are great potentials for power generation around the world which produce less environmental problems. Hydroelectric power energy has covered 24% of the electrical energy in 2013. The proportion of this kind of energy is increasing rapidly. The amount of energy produced in different seasons of the year and different hours of the day is one of the most important issues in water plants. In other words, determining the capacity of installation (design discharge) is one of the important factors in the design of power plants. In this research, a developed algorithm for simulating hydropower energy production has been developed using MATLAB application. This developed model has been used for hydropower modeling. In such a situation, simulating energy production of the dam has been conducted for different power plant installation capacity and finally with applying reliability index of 90%, the installation capacity of the power plant equals 2.7 Kilowatt. In this installation capacity, initial energy and surplus has occurred in most months. Furthermore, in 33% of cases that the reservoir is in its maximum balance, surplus energy has been generated. Moreover, the scale of initial energy and the average surplus energy respectively equals to 20.80 and 13.2 Gigawatt hours annually on 24-h basis. By changing the input variables, this algorithm and the developed model can be applied in any single hydropower reservoir system.

     

推求设计降水的随机模拟方法

应用甘南县实测降水数据,采用伽玛分布函数模拟了该县长系列降水数据,利用模拟出的数据推求了该县多个月份指定频率的设计降水量。研究成果表明,应用随机模拟的方法确定设计降水是可行的,与配线法相比,本文方法更加直观,且推求出的设计降水与配线法所得的结果基本一致,为推求设计降水提供了一种新方法。