Basin/Reservoir System Integration for Real Time Reservoir Operation

This paper demonstrates the basin/reservoir system integration as a decision support system for short term operation policy of a multipurpose dam. It is desired to re-evaluate and improve the current operational regulation of the reservoir with respect to water supply and flood control especially for real time operation. The most innovative part of this paper is the development of a decision support system (DSS) by the integration of a hydrological (HEC-HMS) and reservoir simulation model (HEC-ResSim) to guide the professional practitioners during the real time operation of a reservoir to meet water elevation and flood protection objectives. In this context, a hybrid operating strategy to retain maximum water elevation is built by shifting between daily and hourly decisions depending on real time runoff forecasts. First, a daily hydro-meteorological rule based reservoir simulation model (HRM) is developed for both water supply and flood control risk. Then, for the possibility of a flood occurrence, hourly flood control rule based reservoir simulation model (FRM) is used. The DSS is applied on Yuvac?k Dam Basin which has a flood potential due to its steep topography, snow potential, mild and rainy climate in Turkey. Numerical weather prediction based runoff forecasts computed by a hydrological model together with developed reservoir operation policy are put into actual practice for real time operation of the reservoir for March – June, 2012. According to the evaluations, proposed DSS is found to be practical and valuable to overcome subjective decisions about reservoir storage.     

Technical Communication: Two-Phase Stochastic Dynamic Programming Model for Optimal Operation of Irrigation Reservoir

A two-phase stochastic dynamic programming model is developed for optimal operation of irrigation reservoirs under a multicrop environment. Under a multicrop environment, the crops compete for the available water whenever the water available is less than the irrigation demands. The performance of the reservoir depends on how the deficit is allocated among the competing crops. The proposed model integrates reservoir release decisions with water allocation decisions. The water requirements of crops vary from period to period and are determined from the soil moisture balance equation taking into consideration the contribution of soil moisture and rainfall for the water requirements of the crops. The model is demonstrated over an existing reservoir and the performance of the reservoir under the operating policy derived using the model is evaluated through simulation.     

Improved Reservoir Operation Using Hybrid Genetic Algorithm and Neurofuzzy Computing

A hybrid genetic and neurofuzzy computing algorithm was developed to enhance efficiency of water management for a multipurpose reservoir system. The genetic algorithm was applied to search for the optimal input combination of a neurofuzzy system. The optimal model structure is modified using the selection index (SI) criterion expressed as the weighted combination of normalized values of root mean square error (RMSE) and maximum absolute percentage of error (MAPE). The hybrid learning algorithm combines the gradient descent and the least-square methods to train the genetic-based neurofuzzy network by adjusting the parameters of the neurofuzzy system. The applicability of this modeling approach is demonstrated through an operational study of the Pasak Jolasid Reservoir in Pasak River Basin, Thailand. The optimal reservoir releases are determined based on the reservoir inflow, storage stage, sideflow, diversion flow from the adjoining basin, and the water demand. Reliability, vulnerability and resiliency are used as indicators to evaluate the model performance in meeting objectives of satisfying water demand and maximizing flood prevention. Results of the performance evaluation indicate that the releases predicted by the genetic-based neurofuzzy model gave higher reliability for water supply and flood protection compared to the actual operation, the releases based on simulation following the current rule curve, and the predicted releases based on other approaches such as the fuzzy rule-based model and the neurofuzzy model. Also the predicted releases based on the newly developed approach result in the lowest amount of deficit and spill indicating that the developed modeling approach would assist in improved operation of Pasak Jolasid Reservoir.     

A Fuzzy Stochastic Dynamic Nash Game Analysis of Policies for Managing Water Allocation in a Reservoir System

In this paper a fuzzy dynamic Nash game model of interactions between water users in a reservoir system is presented. The model represents a fuzzy stochastic non-cooperative game in which water users are grouped into four players, where each player in game chooses its individual policies to maximize expected utility. The model is used to present empirical results about a real case water allocation from a reservoir, considering player (water user) non-cooperative behavior and also same level of information availability for individual players. According to the results an optimal allocation policy for each water user can be developed in addition to the optimal policy of the reservoir system. Also the proposed model is compared with two alternative dynamic models of reservoir optimization, namely Stochastic Dynamic Programming (SDP) and Fuzzy-State Stochastic Dynamic programming (FSDP). The proposed modeling procedures can be applied as an appropriate tool for reservoir operation, considering the interaction among the water users as well as the water users and reservoir operator.     

A combined hydraulic and biological SBR model

A sequencing batch reactor (SBR) model was developed consisting of six continuous stirred tank reactors which describe the hydraulic flow patterns occurring in different SBR phases. The model was developed using the results of computational fluid dynamics (CFD) simulation studies of an SBR reactor under a selection of dynamic operational phases. Based on the CFD results, the model structure was refined and a simplified 'driver' model to allow one to mimic the flow pattern driven by the external operational conditions (influent, aeration, mixing) was derived. The resulting model allows the modeling of biological processes, settlement and hydraulic conditions of cylindrical SBRs.     

基于MATLAB/xPC Target的抽水蓄能机组调速实时仿真系统

利用MATLAB软件提供的Simulink,RTW,xPC Target等工具箱建立了抽水蓄能机组的实时仿真模型,并通过输入/输出接口电路将实时仿真模型与实际抽水蓄能机组调速器相连接,构成了一个半物理实时仿真系统。利用某电站抽水蓄能机组参数对该系统进行了测试验证,结果表明,该实时仿真系统建模方便、能自动生成高效仿真程序、参数调整灵活、试验曲线与原型机组试验曲线吻合度高,可作为调速器开发设计阶段的试验平台,以及试验验收阶段机组动态特性的测试系统。     

Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression

The reservoir optimal operation depends on not only specific characteristics of reservoirs and hydropower stations but also stochastic inflows. The key issue of actual hydropower operation is to make an approximate optimal decision triggered by limited inflow forecasts. To implement actual optimal operation of hydropower system with limited inflows forecast, this paper makes use of Support Vector Regression (SVR) to derive optimal operating rules. To improve the performance of SVR, parameters in SVR model are calibrated with grid search and cross validation techniques. The trained SVR model describes the complex nonlinear relationships between reservoir operation decisions and factors by considering both generalization and regression performance, which overcomes local optimization and over fitting deficits. Hybrid programming platform is further developed to implement system simulation. This SVR model along with simulation platform is applied to the largest hydropower base in China – Jinsha system. Three scenarios are developed for comparison: deterministic optimal operation, SVR based simulation with calibrated parameters, SVR based simulation with default parameters. Comprehensive evaluation indicates that, operating rules derived from SVR presents a reliable performance in system power generation and output processes with respect to ideal deterministic results, especially when the parameters are calibrated. Hybrid programming technique provides a feasible and compatible platform for future research.     

Evaluation of Real-Time Operation Rules in Reservoir Systems Operation

Reservoir operation rules are logical or mathematical equations that take into account system variables to calculate water release from a reservoir based on inflow and storage volume values. In fact, previous experiences of the system are used to balance reservoir system parameters in each operational period. Commonly, reservoir operation rules have been considered to be linear decision rules (LDRs) and constant coefficients developed by using various optimization procedures. This paper addresses the application of real-time operation rules on a reservoir system whose purpose is to supply total downstream demand. Those rules include standard operation policy (SOP), stochastic dynamic programming (SDP), LDR, and nonlinear decision rule (NLDR) with various orders of inflow and reservoir storage volume. Also, a multi-attribute decision method, elimination and choice expressing reality (ELECTRE)-I, with a combination of indices, objective functions, and reservoir performance criteria (reliability, resiliency, and vulnerability) are used to rank the aforementioned rules. The ranking method employs two combinations of indices: (1) performance criteria and (2) objective function and performance criteria by using the same weights for all criteria. Results show that the NLDR gives an appropriate rule for real-time operation. Moreover, NLDR validation is presented by testing predefined curves for dry, normal, and wet years.     

Multivariate Bayesian Regression Approach to Forecast Releases from a System of Multiple Reservoirs

This research presents a model that simultaneously forecasts required water releases 1 and 2 days ahead from two reservoirs that are in series. In practice, multiple reservoir system operation is a difficult process that involves many decisions for real-time water resources management. The operator of the reservoirs has to release water from more than one reservoir taking into consideration different water requirements (irrigation, environmental issues, hydropower, recreation, etc.) in a timely manner. A model that forecasts the required real-time releases in advance from a multiple reservoir system could be an important tool to allow the operator of the reservoir system to make better-informed decisions for releases needed downstream. The model is developed in the form of a multivariate relevance vector machine (MVRVM) that is based on a sparse Bayesian regression model approach. With this Bayesian approach, a predictive confidence interval is obtained from the model that captures the uncertainty of both the model and the data. The model is applied to the multiple reservoir system located in the Lower Sevier River Basin near Delta, Utah. The results show that the model learns the input–output patterns with high accuracy. Computing multiple-time-ahead predictions in real-time would require a model which guarantees not only good prediction accuracy but also robustness with respect to future changes in the nature of the inputs data. A bootstrap analysis is used to guarantee good generalization ability and robustness of the MVRVM. Test results demonstrate good performance of predictions and statistics that indicate robust model generalization abilities. The MVRVM is compared in terms of performance and robustness with another multiple output model such as Artificial Neural Network (ANN).     

流域洪水调控计算的组态耦合技术与应用

为快速应对流域洪水调控的不确定性计算需求,对流域防洪体系进行数字化建模,将复杂的洪水调控任务分解为相互独立的模型算法组件,研究不同洪水调控场景下防洪对象与模型组件的动态适配技术,提出多类型洪水调控计算的组态耦合方法。结合长江上游防洪体系的水库调蓄与水流传播综合分析情景,对水库群的洪水调度、回水模拟及河道洪水演进动态耦合计算进行实例应用,可大幅提升作业响应速度,任务配置灵活,适应性强,复用度高,对流域洪水的智能调控分析和会商研判决策具有重要支撑作用。     

基于系统动力学的城市内涝灾害应急管理模型

采用系统动力学(SD)方法建立城市内涝灾害应急管理SD模型。在确定模型变量权重的基础上,通过构建模型方程式并绘制内涝灾害因果回路图和存量流量图实现对事件动态模拟仿真和敏感性分析。将构建的SD模型用于西安市一场典型内涝灾害事件的仿真分析,结果表明：随着时间增长,通过模拟仿真增加对技术因素、社会因素、管理因素和自然因素的管控,城市内涝灾害应急管理效果趋于变好;SD模型中不同变量对城市内涝灾害应急管理影响存在差异,需要不断完善应急预案,加强城市排水管网建设,提高应急决策时效性。     

Multi Objective Simulation-Optimization Approach in Pollution Spill Response Management Model in Reservoirs

In this study, a Pollution Spill Response Management Model (PSRMM) is developed to provide an emergency response on reservoir operation during accidental injection of hazardous material to reservoirs. PSRMM consist of spatial system analyzing (SSA) model, 2D hydrodynamic and water quality simulation model (CE-QUAL-W2), and multi-objective particle swarm optimization (MOPSO) algorithm. CE-QUAL-W2 model is applied for spatial and temporal analysis of water body in simulation routine of PSRMM. Also, in an advanced modeling framework, CE-QUAL-W2 is coupled with MOPSO algorithm to obtain desirable near optimal reservoir operation strategy and/or emergency planning in selective withdrawal framework. The simulation-optimization (SO) routine of PSRMM provides pareto optimum reservoir operation strategy in selective scheme to minimize reservoir cleanup time and to reduce the magnitude and frequency of water quality standard violations. The proposed tool is applied in Ilam reservoir in Iran, as a multipurpose hydraulic project providing water for drinking, irrigation, and flood control during an accident spill of conservative hazardous material. Different scenarios are defined and tested employing the proposed PSRMM for managing accidental spill of conservative pollutant into the reservoir.     

Water Supply Reservoir Operation by Combined Genetic Algorithm – Linear Programming (GA-LP) Approach

Multi-reservoir operation planning is a complex task involving many variables, objectives, and decisions. This paper applies a hybrid method using genetic algorithm (GA) and linear programming (LP) developed by the authors to determine operational decisions for a reservoir system over the optimization period. This method identifies part of the decision variables called cost reduction factors (CRFs) by GA and operational variables by LP. CRFs are introduced into the formulation to discourage reservoir depletion in the initial stages of the planning period. These factors are useful parameters that can be employed to determine operational decisions such as optimal releases and imports, in response to future inflow predictions. A part of the Roadford Water Supply System, UK, is used to demonstrate the performance of the GA-LP method in comparison to the RELAX algorithm. The proposed approach obtains comparable results ensuring non zero final storages in the larger reservoirs of the Roadford Hydrosystem. It shows potential for generating operating policy in the form of hegging rules without a priori imposition of their form.     

A combined stochastic dynamic programming-statistical disaggregation approach applied to multiple reservoir systems

The stochastic dynamic programming (SDP) method faces computational difficulties when used to determine the optimal operation of multiple storages. A new approach, a combined SDP-statistical disaggregation approach is introduced to determine releases for a special situation relating to multiple reservoir systems, that is, for a system of multiple storages where operational data are available. The approach consists of defining an equivalent single reservoir which represents the system of multiple reservoirs. The optimal releases from the equivalent single reservoir are derived by the use of SDP. Disaggregation of the optimal releases from the equivalent single reservoir, to produce the releases from the individual storages is based on historical operational data. The Melbourne (Australia) water supply system is considered as the example. The releases derived from the combined SDP-statistical disaggregation approach are tested by operating a simulation model, and the conclusion is made that the approach produces satisfactory releases for a system of multiple reservoirs where operational data are available. The method cannot be applied to existing systems where insufficient or no operational data are available, or to proposed systems where operational data are not available. The method uses a small amount of computer time.     

广东省小型水库动态监管系统的应用与实践

水库动态监管系统基于实用、低成本、一体化集成的设计理念,将图像信息集成到传统的水位、雨量信息采集设备中,形成水位、雨量、图像、水温、气温、气压等综合信息采集和传输一体化的采集设备,并设计了基于地理信息系统和数据库的信息管理平台.通过水库动态监管项目的实施,能够及时了解掌握各水库基础资料、运行管理现状、安全隐患等情况,可实现广东省大、中、小型水库的全天候实时动态管理.     

An alternative approach to the operation of multinational reservoir systems: Application to the Amistad &; Falcon system (Lower Rio Grande/Río Bravo)

An optimization approach for the operation of international multi-reservoir systems is presented. The approach uses Stochastic Dynamic Programming (SDP) algorithms – both steady-state and real-time – to develop two models. In the first model, the reservoirs and flows of the system are aggregated to yield an equivalent reservoir, and the obtained operating policies are disaggregated using a non-linear optimization procedure for each reservoir and for each nation's water balance. In the second model a multi-reservoir approach is applied, disaggregating the releases for each country's water share in each reservoir. The non-linear disaggregation algorithm uses SDP-derived operating policies as boundary conditions for a local time-step optimization. Finally, the performance of the different approaches and methods is compared. These models are applied to the Amistad-Falcon International Reservoir System as part of a binational dynamic modeling effort to develop a decision support system tool for a better management of the water resources in the Lower Rio Grande Basin, currently enduring a severe drought.     

An Optimal Operation Model for Hydropower Stations Considering Inflow Forecasts with Different Lead-Times

To make full use of inflow forecasts with different lead times, a new reservoir operation model that considers the long-, medium- and short-term inflow forecasts (LMS-BSDP) for the real-time operation of hydropower stations is presented in this paper. First, a hybrid model, including a multiple linear regression model and the Xinanjiang model, is developed to obtain the 10-day inflow forecasts, and ANN models with the circulation indexes as inputs are developed to obtain the seasonal inflow forecasts. Then, the 10-day inflow forecast is divided into two segments, the first 5 days and the second 5 days, and the seasonal inflow forecast is deemed as the long-term forecast. Next, the three inflow forecasts are coupled using the Bayesian theory to develop LMS-BSDP model and the operation policies are obtained. Finally, the decision processes for the first 5 days and the entire 10 days are made according to their operation policies and the three inflow forecasts, respectively. The newly developed model is tested with the Huanren hydropower station located in China and compared with three other stochastic dynamic programming models. The simulation results demonstrate that LMS-BSDP performs best with higher power generation due to its employment of the long-term runoff forecast. The novelties of the present study lies in that it develops a new reservoir operation model that can use the long-, medium- and short-term inflow forecasts, which is a further study about the combined use of the inflow forecasts with different lead times based on the existed achievements.

     

基于水循环的分布式水资源调配模型开发与应用

自以水循环为基础的水资源动态配置模式提出以来,一批基于耦合分布式水文模型的水资源配置模型被先后提出,但其采用的耦合方法往往忽视了经济社会用水过程与天然水文过程之间的动态反馈作用。本文通过改进SWAT模型,并嵌合水资源配置模块,开发了基于水循环的分布式水资源调配模型（Water resources allocation and regulation model based on the SWAT,SWAT-WARM）,从模型结构、耦合方法、配置规则等方面系统描述了模型的双向耦合原理。以唐河流域为例开展模型的构建与应用研究,采用包含河道流量过程、特征频率径流总量、国民经济用水量和水资源开发利用量的多指标校验方法验证模型的性能,在此基础上,分析了不同时空尺度的水资源配置结果以及全流域年度水循环转化情况。分析结果表明,该模型通过分布式水文模拟和水资源配置模拟的动态结合,能够描述“自然-社会”水资源复杂系统的实时互馈过程,可为流域水资源精细化管理提供技术支撑。     

基于VB二次开发技术的混凝土坝浇筑仿真模型构建

鉴于AutoCAD的强大建模功能并具有二次开发接口,将AutoCAD与仿真系统相结合,运用可视化建模与参数化建模方法建立具备扩展属性的三维实体静态模型和坝体自动剖分的动态模型,增强了系统模型精确性,提高了仿真模拟的效率。利用VB.NET进行了混凝土坝浇筑仿真模型系统的开发,并将其应用到某工程,验证了该系统的有效性。     

Model for reservoir operations during periods of high flow

A combined dynamic programming optimization and hydraulic simulation model is presented for the analysis of the operation of hydroelectric reservoir facilities during periods of flood flows. The model is specifically designed to analyze the impacts of reservoir operations on upstream flooding and to consider complex reservoir outlet works. The model was applied to analyze the design and operational strategies for the Visegrad Hydroelectric Project in Yugoslavia. Results of the analysis indicated that the most economical means of flood protection for upstream areas was a combination of flood protection structures and a lowering of the reservoir storage level in anticipation of flood flows.