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.     

基于流溪河模型的乐昌峡水库入库洪水预报模型研究

采用流溪河模型构建乐昌峡水库入库洪水预报模型,通过"粒子群(PSO)"算法优选模型参数,并对实测洪水过程进行了模拟,对比模型性能。研究发现,采用流溪河模型的乐昌峡水库入库洪水预报性能优良,可满足乐昌峡水库入库洪水预报对精度的要求;模型参数优选可明显提高乐昌峡水库入库洪水预报流溪河模型的洪水模拟精度;"粒子群"算法具有很强的全局优化能力,快速的计算收敛能力,参数优选中种群进化次数在30次以内;乐昌峡水库的建成运行产生了一定的水库洪水效应,10场洪水平均峰现时间提前1.3 h,次洪径流系数增加1.596%,洪峰流量增加0.207%。该模型可用于同类水库入库洪水预报。     

Derivation of Optimal Hedging Rules for a Water-supply Reservoir through Compromise Programming

This study derives optimal hedging rules for simultaneously minimizing short- and long-term shortage characteristics for a water-supply reservoir. Hedging is an effective measure to reduce a high-percentage single period shortage, but at a cost of more frequent small shortages. Thus simultaneously minimizing the maximum monthly shortage and the shortage ratio (defined as the ratio of total shortages to total demands) over the analysis horizon is the operation goal of a water-supply reservoir to derive optimal hedging rules. Two types of hedging are explored in this study: the first uses water availability defined as storage plus inflow, while the second depends on the potential shortage conditions within a specific future lead-time period. The compromise programming is employed to solve this conflicting multiobjective problem. The optimal hedging rules under given reservoir inflow are derived first. Because future inflow cannot be known exactly in advance, the monthly decile inflows are suggested as a surrogate for forecast of future inflows in hedging rules for real-time reservoir operations. The results show that the suggested method can effectively achieve the reservoir operation goal. The merits of the proposed methodology are demonstrated with an application to the Shihmen reservoir in Taiwan.     

Real-Time Operation of Reservoir System by Genetic Programming

Reservoir operation policy depends on specific values of deterministic variables and predictable actions as well as stochastic variables, in which small differences affect water release and reservoir operation efficiency. Operational rule curves of reservoir are policies which relate water release to the deterministic and stochastic variables such as storage volume and inflow. To operate a reservoir system in real time, a prediction model may be coupled with rule curves to estimate inflow as a stochastic variable. Inappropriate selection of this prediction model increases calculations and impacts the reservoir operation efficiency. Thus, extraction of an operational policy simultaneously with inflow prediction helps the operator to make an appropriate decision to calculate how much water to release from the reservoir without employing a prediction model. This paper addresses the use of genetic programming (GP) to develop a reservoir operation policy simultaneously with inflow prediction. To determine a water release policy, two operational rule curves are considered in each period by using (1) inflow and storage volume at the beginning of each period and (2) inflow of the 1^st, 2^nd, 12^th previous periods and storage volume at the beginning of each period. The obtained objective functions of those rules have only 4.86 and 0.44?% difference in the training and testing data sets. These results indicate that the proposed rule based on deterministic variables is effective in determining optimal rule curves simultaneously with inflow prediction for reservoirs.     

Optimal Pre-storm Flood Hedging Releases for a Single Reservoir

Flood hedging reservoir operation is when a pre-storm release creates a small flood downstream to reduce the likelihood of a more damaging but uncertain larger flood in the future. Such pre-storm releases before a flood can increase reservoir storage capacity available to capture more severe flood flows, but also can immediately increase downstream flood damage and reduce stored water supply. This study develops an optimization model for pre-storm flood hedging releases and examines some necessary theoretical conditions for optimality, considering hydrologic uncertainty from flood forecasts and engineering uncertainty from flood failures. Theoretically, the ideal optimality condition for pre-storm flood hedging releases is where the current marginal damage from the hedging release equals the future expected marginal damage from storm releases. Additional water supply losses due to pre-storm releases tend to reduce pre-storm flood hedging releases. The overall flood damage cost to be minimized must be a convex function of pre-storm hedging releases for flood hedging to be optimal. Such convexity is determined by the overall flood risk together with the probability distribution of storm forecasts. Increasing the convexity of the failure probability function can induce more pre-storm hedging release. Categorized by flood risk likelihood downstream, forecasted storms that are large, but not yet overwhelming flood management systems, drive optimal flood hedging operation. A wide range of near-optimal hedging releases is observed in numerical examples, providing options for more rational water resources management decisions.     

三峡水库实时调度水文气象预报应用风险及控制

为量化水文气象预报误差对水库实时预报调度的影响,以三峡水库为例,基于其历年水文气象预报信息的误差分析成果,假定入库过程,并叠加对应不同概率的预报误差,以此作为水库调洪演算模型的输入。分析了不同预见期、不同保证率水文气象误差条件下,不超过风险控制点的库水位指标,提出了三峡水库实时预报调度风险控制策略,可为水库科学调度提供参考。     

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.     

Enhancing Inflow Forecasting Model at Aswan High Dam Utilizing Radial Basis Neural Network and Upstream Monitoring Stations Measurements

The Nile River is considered the main life artery for so many African countries especially Egypt. Therefore, it is of the essence to preserve its water and utilize it very efficiently. Developing inflow-forecasting model is considered the technical way to effectively achieve such preservation. The hydrological system of the Nile River under consideration has several dams and barrages that are equipped with control gates. The improvement of these hydraulic structures’ criteria for operation can be assessed if reliable forecasts of inflows to the reservoir are available. Recently, the authors developed a forecasting model for the natural inflow at Aswan High Dam (AHD) based on Artificial Intelligence (AI). This model was developed based on the historical inflow data of the AHD and successfully provided accurate inflow forecasts with error less than 10%. However, having several forecasting models based on different types of data increase the level of confidences of the water resources planners and AHD operators. In this study, two forecasting model approach based on Radial Basis Function Neural Network (RBFNN) method for the natural inflow at AHD utilizing the stream flow data of the monitoring stations upstream the AHD is developed. Natural inflow data collected over the last 30 years at four monitoring stations upstream AHD were used to develop the model and examine its performance. Inclusive data analysis through examining cross-correlation sequences, water traveling time, and physical characteristics of the stream flow data have been developed to help reach the most suitable RBFNN model architecture. The Forecasting Error (FE) value of the error and the distribution of the error are the two statistical performance indices used to evaluate the model accuracy. In addition, comprehensive comparison analysis is carried out to evaluate the performance of the proposed model over those recently developed for forecasting the inflow at AHD. The results of the current study showed that the proposed model improved the forecasting accuracy by 50% for the low inflow season, while keep the forecasting accuracy in the same range for the high inflow season.     

Seasonal Inflow Forecasts Using Gridded Precipitation and Soil Moisture Information: Implications for Reservoir Operation

Water Resources Management - Reservoir inflow forecasts are important for guiding reservoir operation. This study proposes an integrated framework of incorporating different forms of seasonal...     

漳河水库动库容研究

依据漳河水库入库洪水计算中存在的主要问题,提出综合考虑入流及出流影响的漳河观音寺水库动态库容计算方法,并建立了模型的求解方程与动态水位-库容曲线。在实际应用中,较好地解决了由静态水位-库容曲线求得的入库水量失真的问题。研究成果为水库洪水预报提供了新的技术方法,有利于多种方法对水库洪水预报进行相互佐证,提高了水库洪水预报调度水平。     

大伙房水库计算机网络系统的建设与应用

文章介绍了大伙房水库计算机网络系统建设的结构、组成和特点及其关键应用,并分析了系统的运行效益。大伙房水库计算机网络系统是将水文自动测报、洪水预报与调度、大坝安全监测、远程视频监控、防汛会商、供水计量、闸门控制、办公自动化等子系统有机地集合成一个一体化的、功能强大的新型系统,为水库的控制运行与管理提供了全面的信息化服务。     

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.

     

三峡水库水文气象预报不确定性及误差分布分析

准确、及时的水文气象预报信息是水库实时预报调度的基础和技术支撑。基于长江水利委员会水文局发布的三峡水库历年短中期入库流量预报成果,综合评定了预报精度和水平,分析了降雨量级、落区及入库流量级别等因素对预报误差的影响,比较了正态分布和非参数估计两种方法用于估计预报相对误差概率密度函数的效果。结果显示,采用非参数估计推求的概率密度函数与样本拟合程度高,可应用于三峡水库水文气象预报定量风险管理。     

Reservoir Operation Modelling with Fuzzy Logic

In this article, a fuzzy rule based model is developed for the operation of a single purpose reservoir. The model operates on an 'if – then' principle, where the 'if' is a vector of fuzzy premises and the 'then' is a vector of fuzzy consequences. The steps involved in the development of the model include, construction of membership functions for the inflow, storage, demand and the release, formulation of fuzzyrules, implication and defuzzification. The methodology is illustrated through the case study of the Malaprabha irrigation reservoir in Karnataka, India. Reservoir storage, inflow, and demands are used as premises and the release as the consequence.Simulated reservoir operation with a steady state policy provides the knowledge base necessary for the formulation of the Fuzzy rules.     

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.     

Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations

This study has evaluated the effects of improved, hedging-integrated reservoir rule curves on the current and climate-change-perturbed future performances of the Pong reservoir, India. The Pong reservoir was formed by impounding the snow- and glacial-dominated Beas River in Himachal Pradesh. Simulated historic and climate-change runoff series by the HYSIM rainfall-runoff model formed the basis of the analysis. The climate perturbations used delta changes in temperature (from 0° to +2 °C) and rainfall (from ?10 to +10 % of annual rainfall). Reservoir simulations were then carried out, forced with the simulated runoff scenarios, guided by rule curves derived by a coupled sequent peak algorithm and genetic algorithms optimiser. Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. The results show that the historic vulnerability reduced from 61 % (no hedging) to 20 % (with hedging), i.e., better than the 25 % vulnerability often assumed tolerable for most water consumers. Climate change perturbations in the rainfall produced the expected outcomes for the runoff, with higher rainfall resulting in more runoff inflow and vice-versa. Reduced runoff caused the vulnerability to worsen to 66 % without hedging; this was improved to 26 % with hedging. The fact that improved operational practices involving hedging can effectively eliminate the impacts of water shortage caused by climate change is a significant outcome of this study.     

Sensitivity of reservoir operation performance to climatic change

The potential impacts of changing climatic conditions on the operational performance of water resource systems was investigated in this paper. A multi-site streamflow generation model was used to synthesize potential monthly flow sequences reflecting two different sets of climatic conditions. The generated data were subsequently employed as input to a reservoir operation model that was used to determine the reservoir response to the inflow resulting from the implementation of the reservoir operating policy. The performance of an example reservoir system, the Shellmouth Reservoir located in the Canadian province of Manitoba, was evaluated and compared for the two sets of conditions. The operational performance was evaluated in terms of the reliability of the system for meeting the three purposes of the actual reservoir. The reservoir performance was determined to be sensitive to the inflow data. The results indicate that climatic change has potentially important implications for the operation of the example reservoir system.     

刘家峡水库对水沙变异影响分析

利用刘家峡水库运行前后进出库控制站的水文资料,对水库运行以来的径流泥沙特征进行了分析。研究表明:(1)水库运行对进出库年径流量影响很小,对年内分配影响大;(2)单库运行期水库蓄水拦沙,出库洪峰流量削减,年内径流量分配发生变化,泥沙量大幅度减少;(3)龙羊峡水库运行后的联合运行期,洪峰流量略有削减,年内蓄水过程改变后仍有一定的拦沙作用,出库含沙量较单库运行期增加;(4)水库运行减小了出库含沙量,并没有改变出库含沙量与入库含沙量的线性关系。     

Nominees as Candidates for the Executive Board 1989–1991

ABSTRACT

Principles of sustainable development are inviting a change in the approach used for reservoir management. Instead of designing and planning new reservoirs, more emphasis will be placed on management of existing reservoirs. Reservoir storage reallocation and reassessment of reservoir operational rules are considered to be the two main problems to be addressed by reservoir research in the near future. Appropriate techniques for solving these two problems are necessary An attempt at developing a sound methodology for a reservoir reassessment has been presented here. A simulation approach, based on the four probability criteria, has been used in this context for storage analysis. Reservoir management strategies have been reassessed using an implicit stochastic optimization model. The methodology has been applied to Wonogiri Reservoir located in Central Java, Indonesia. Analysis of the storage capacity indicated that the current capacity is larger than that required for the irrigation of an area of 25,319 ha, corresponding to the Wonogiri reservoir final development phase. Thus, the present size of the reservoir allows for additional multipurpose use of the reservoir storage. Optimization of the reservoir yield demonstrated that the reservoir can provide for municipal and industrial water supply and hydropower generation in addition to the current use af reservoir storage for irrigation water supply.