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.     

Water Transfer Triggering Mechanism for Multi-Reservoir Operation in Inter-Basin Water Transfer-Supply Project

This paper proposes a new water transfer triggering mechanism for multi-reservoir system to divert water from abundant to scarce regions with a constant diversion flow in an inter-basin water transfer-supply project. Taking into account of the uncertain nature of inflow, the storage of reservoir is taken as a signal for decision-making to indicate water abundance or water scarcity. In this study, a set of rule curves based on storage of donor reservoir and storage of recipient reservoir are used together to determine when to start water transfer. To initiate water diversion to each recipient reservoir effectively, several water transfer rule curves of the donor reservoir are set for each recipient reservoir respectively in the multi-reservoir system with one donor reservoir and several recipient reservoirs, which is the main difference in comparison with other water transfer triggering mechanisms. In addition, a systematic framework is developed to integrate the water transfer rule curves with hedging rule curves to simultaneously solve the water transfer and water supply problems, since they interact with each other during the operation process. In order to verify the utility of the new water transfer triggering mechanism, an inter-basin water transfer-supply project in China is used as a case study and an improved particle swarm optimization algorithm (IPSO) with a simulation model is adopted for optimizing the decision variables. The results show that the proposed water transfer triggering mechanism can improve the operation performances of the inter-basin system.     

Assessment of Stochastic Operation Optimization for Reservoirs of Contrasting Scales

Deriving optimal release policies for dams and corresponding reservoirs is crucial for the sustainable water resources management of a region as they directly control the distribution of water to several users. Mathematical optimization algorithms can help in finding efficient reservoir operating strategies taking into account complex system constraints and hydrologic uncertainty. The robustness of operation optimization models may be influenced by physical reservoir characteristics such as size and scale and the effectiveness of a model for a particular case study does not always guarantee the same level of success for another application. This research focused on assessing the applicability of an implicit stochastic optimization (ISO) procedure to derive rule curves for two different dams of contrasting reservoir scales in terms of physical and operational characteristics. The results demonstrated the feasibility of the proposed technique for both small- and large-scale systems in view of the lower vulnerability provided by the ISO-derived policies in contrast to operations carried out by the standard reservoir operating policy as well as the proximity of the ISO operations with those by perfect-forecast deterministic optimization. The ISO procedure also provided operating rules similar to, and even less vulnerable than, those derived by stochastic dynamic programming.     

Single Reservoir Operating Policies Using Genetic Algorithm

To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. As every model has its own limitations, the selection of appropriate model for derivation of reservoir operating rule curves is difficult and most often there is a scope for further improvement as the model selection depends on data available. Hence, evaluation and modifications related to the reservoir operation remain classical. In the present study a Genetic Algorithm model has been developed and applied to Pechiparai reservoir in Tamil Nadu, India to derive the optimal operational strategies. The objective function is set to minimize the annual sum of squared deviation form desired irrigation release and desired storage volume. The decision variables are release for irrigation and other demands (industrial and municipal demands), from the reservoir. Since the rule curves are derived through random search it is found that the releases are same as that of demand requirements. Hence based on the present case study it is concluded that GA model could perform better if applied in real world operation of the reservoir.     

Reservoir Operation Incorporating Hedging Rules and Operational Inflow Forecasts

Reservoir operation incorporating a naïve hedging strategy and operational inflow forecasting is studied in this paper. Gridded precipitation forecasts from climate model, ECHAM4.5, are used as potential predictors for reservoir inflow forecasting. In building a statistical predicting model, principal component analysis (PCA) is used to reduce the dimension of the regression model. Performance evaluation indices, including water supply satisfaction ratio, environmental flow satisfaction ratio, end-of-month storage satisfaction ratio and flood prevention capacity index, are defined. Three scenarios where a naïve hedging operation rule under different set of reservoir inflow are investigated. These are evaluated for a water supply reservoir, Falls Lake Reservoir, at Neuse River in the southeast United State. Reservoir simulation with monthly average inflow serves as a benchmark. The utility of operational inflow forecasts is quantified by the improvements of performance indices. Results show that reservoir operation under perfect inflow forecasting has the highest values for most indices. Compared to climatology, operational inflow forecasts result in higher index values. Among all the performance indices, end-of-month storage satisfaction ratio is the most sensitive index to inflow information. Limitation of this study and further work is also discussed.     

随机约束线性规划在水库综合利用中的应用

由于水库入流的不确定性，各用水目标的基本要求（目标放水量）将体现在年内各时期水库放水的随机约束上，配合水库线民生蓄泄水决策规则，将全部随机约束进行确定性等效转换，得到线性规划模型，经多次解析，就可得到水主加容量一定情况下的最优运行规则，针对大型水资源工程综合利用的多目标要求，研究建立了随机约束线性规划模型，以求解水库最优运行规划的方法，并以西南地区某大型综合利用水库为例，对模型进行求解，该方法随机     

Simulation-optimization model of reservoir operation based on target storage curves

This paper proposes a new storage allocation rule based on target storage curves. Joint operating rules are also proposed to solve the operation problems of a multi-reservoir system with joint demands and water transfer-supply projects. The joint operating rules include a water diversion rule to determine the amount of diverted water in a period, a hedging rule based on an aggregated reservoir to determine the total release from the system, and a storage allocation rule to specify the release from each reservoir. A simulation-optimization model was established to optimize the key points of the water diversion curves, the hedging rule curves, and the target storage curves using the improved particle swarm optimization （IPSO） algorithm. The multi-reservoir water supply system located in Liaoning Province, China, including a water transfer-supply project, was employed as a case study to verify the effectiveness of the proposed join operating rules and target storage curves. The results indicate that the proposed operating rules are suitable for the complex system. The storage allocation rule based on target storage curves shows an improved performance with regard to system storage distribution.     

Water Management of Irrigation Dams Considering Climate Variation: Case Study of Zayandeh-rud Reservoir, Iran

Dependency of reservoir operation on the climate variation occurs especially in regions, where agricultural demand has a significant share of the total water demands. The variability between demands that are based on annual climate conditions may be larger than the uncertainty associated with other explanatory variables in long-term operation of an irrigation dam. This paper proposed a rule curves to the water managers of the Zayandeh-rud reservoir in Iran in long-lead reservoir operation. A regional optimal allocation of water among different crops and irrigation units is developed. The optimal allocation model is coupled with a reservoir operating model, which is developed based on the certain hedging that deals with the available water and the water demands mutually. This coupled model is able to activate restrictions on allocating water to agricultural demands considering variation of inflow to the reservoir, variation of demands and the economic value of allocating water among different crops and irrigation units. The resulted rule curve is presented with a number of tables for more details and accuracy and a simple curve, which is more useful for operational purpose.     

Optimization of Nebhana Reservoir Water Allocation by Stochastic Dynamic Programming

This study is devoted to the identification of an optimal rule that would permit to improve the water resources management of dam in arid condition. The Nebhana dam is considered in this study as a representative of a set dams situated in such condition. The water storage is used for irrigation purpose. The identification of an optimal rule is based on two opposite objectives: the satisfaction of the irrigation water demand and the safeguard of a minimal water storage in the dam. By considering different weights for these objectives, the stochastic dynamic programming technique was lead to various optimal rules for the water resources management of the Nebhana dam. This technique takes into account the variability of the volume of water inflow to the dam on the basis of their occurrence probability; the water losses by means of forecasting models and the water resources goals using weight coefficients. The identified optimal rule would permit to estimate the necessary water release volume for irrigation by considering the water storage and the decision period.     

Development and application of a simulation model for reservoir management

The success of irrigation system operation and planning depends on accurate quantification of supply and demand, and an equitable distribution of available water. The ultimate aim of this study was to determine how to meet the irrigation water demands if possible or to minimize the gap between the water supply and the demand. Most of the irrigation literature focuses only on the demand and the distribution aspects of this issue Irrigation projects that receive water from reservoirs, however, can be challenging to manage because the annual fluctuations in available water release from a reservoir can have a considerable impact on the irrigation management strategy. In real‐world situations, the reservoir operating rules guide reservoir operators in making actual water release decisions. This study develops a water balance simulation model for reservoir management, as well as testing it for Kangsabati Reservoir, West Bengal, India. Two rule curves for deciding irrigation water available from the reservoir were generated by taking the average and minimum stage values on a daily basis for a 16‐year period (1988–2003). Maintaining a minimum stage of 120.4 m throughout the year served as another rule to decide the release water available for irrigation. The minimum allowable stage of reservoir corresponding to a particular date of the year can be determined from those reservoir specific rule curves generated for irrigation purposes. The maximum permissible water release/outflow for irrigation from the test reservoir was taken as the volume of water available above the minimum allowable stage corresponding to the selected rule curve. The saturated hydraulic conductivity value (K_S) was calibrated to be 4.31 mm day^?1 for Kangsabati Reservoir.     

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.     

A realistic linear decision rule for reservoir management

A generalized linear decision rule is presented which takes into account the aspect of spill in a multi-lag LDR model. The proposed rule incorporates past inflow experience to determine the optimum release rules based on a stochastic (linear) programming optimization model. It also prescribes a procedure of determining spill, should it occur, and the method of adjusting the release policy, accordingly, for the subsequent periods, which are directly affected by the spill of the current period. The use of the rule also makes it possible to produce a specification for a reservoir with a smaller capacity by taking liberal constraints on the reservoir freeboard during the monsoon months. The problem is solved, for the purpose of illustration, using the historical data of a river located in central India. Two synthetic streamflow series of a duration of 50 years each are generated under lognormal flow assumption. The prescribed release rules are applied to a hypothetical reservoir with the optimum capacity determined by the linear programming method, and the generated series as the inflow. The results and findings are quite satisfactory.     

跨流域供水水库群联合调度规则研究

针对跨流域供水水库群联合调度存在的主从递阶结构,提出了调水规则和供水规则相结合的跨流域供水水库群联合调度规则。其中,调水规则由一组基于各水库蓄水量的调水控制线表示,根据其间的相对位置关系,决定是否调水,调水量如何分配等;供水规则由各库供水调度图表示,对应于不同用水户的限制供水线将水库的兴利库容分为若干调度区。建立了适合于主从递阶结构的水库群联合调度二层规划模型,采用并行种群混合进化的粒子群算法对模型进行求解。中国北方某大型跨流域调水工程的实例研究证明了模型的合理性和有效性。     

Improving Implicit Stochastic Reservoir Optimization Models with Long-Term Mean Inflow Forecast

This technical note introduces a reservoir operation model based on implicit stochastic optimization (ISO) in which the release policy is guided by the forecast of the mean inflow for a given future horizon rather than by the prediction of the current-month inflow, such as in typical ISO models. The model also does not require the forecast of all inflows for the future horizon and shows to be more efficient in finding less vulnerable release policies when compared to several other explicit and implicit stochastic procedures.     

Derivation of Aggregation-Based Joint Operating Rule Curves for Cascade Hydropower Reservoirs

Operating rule curves have been widely applied to reservoir operation, due to their ease of implementation. However, these curves are generally used for single reservoirs and have rarely been applied to cascade reservoirs. This study was conducted to derive joint operating rule curves for cascade hydropower reservoirs. Steps in the proposed methodology include: (1) determining the optimal release schedule using dynamic programming to solve a deterministic long-term operation model, (2) identifying the forms of operating rule curves suitable for cascade hydropower reservoirs based on the optimal release schedule, (3) constructing a simulation-based optimization model and then using the non-dominated sorting genetic algorithm-II (NSGA-II) to identify the key points of the operating rule curves, (4) testing and verifying the efficiency of the generated joint operating rule curves using synthetic inflow series. China’s Qing River cascade hydropower reservoirs (the Shuibuya, Geheyan and Gaobazhou reservoirs) were selected for a case study. When compared with the conventional operating rule curves, the annual power generation can be increased by 2.62% (from 7.27 to 7.46 billion kWh) using the observed inflow from 1951 to 2005, as well as by about 1.77% and 2.52% using the synthetic inflows generated from two alternative hydrologic simulation methods. Linear operating rules were also implemented to simulate coordinated operation of the Qing River cascade hydropower reservoirs. The joint operating rule curves were more efficient and reliable than conventional operating rule curves and linear operating rules, indicating that the proposed method can greatly improve hydropower generation and work stability.     

Optimization of Multi-Reservoir Operating Rules for a Water Supply System

To obtain the optimal releases of the multi-reservoir system, two sets of joint operating rules (JOR-I and JOR-II) are presented based on the aggregation-disaggregation approach and multi-reservoir approach respectively. In JOR-I, all reservoirs are aggregated to an equivalent reservoir, the operating rules of which, the release rule of the system is optimized following operating rule curves coupled with hedging rules. Then the system release is disaggregated into each reservoir according to water supply priorities and the dynamic demand partition approach. In JOR-II, a two-stage demand partition approach is applied to allocate the different demand priorities to determine the release from each reservoir. To assess the reliability and effectiveness of the joint operating rules, the proposed rules are applied to a multi-reservoir system in Liaoning province of China. Results demonstrate that JOR-I is suitable for high-dimensional multi-reservoir operation problems with large-scale inflow data, while JOR-II is suitable for low-dimensional multi-reservoir operation problems with small-scale inflow data, and JOR-II performs better than JOR-I but requires more computation time. The research provides guidelines for the management of multi-reservoir system.     

Reliability-based Operation of Reservoirs Using Combined Monte Carlo Simulation Model and a Novel Nature-inspired Algorithm

One of the critical issues in surface water resources management is the optimal operation of dam reservoirs. In recent decades, meta-heuristics algorithms have gained attention as a powerful tool for finding the optimal program for the dam reservoir operation. Increasing demand due to population growth and lack of precipitation for reasons such as climate change has caused uncertainties in the affecting parameters on the planning of reservoirs, which invalidates the operational plans of these reservoirs. In this study, a novel optimization algorithm with the combination of genetic algorithm (GA) and multi-verse optimizer (MVO) called multi-verse genetic algorithm (MVGA) has been developed to solve the optimal dam reservoir operation issue under influence of the joint uncertainties of inflow, evaporation and demand. After validating the performance of MVGA by solving several benchmark functions, MVGA was used to find the optimal operation program of the Amirkabir Dam reservoir in 132 months, in both deterministic and probabilistic states. Minimizing the deficit between downstream demand and release from the reservoir during the operation period was considered as the objective function. Also, the limitations of the reservoir continuity equation, storage volume, and reservoir release equation were applied to the objective function. For modeling the effect of uncertainty, Monte Carlo simulation (MCS) is coupled to MVGA. The results of model implementations showed that the MVGA-MCS model with the best value of the objective function equal to 26 in the 1st rank and MVGA, MVO, and GA, with 15%, 34%, and 46% increase in the value of the objective function compared to the MVGA-MCS stood in the second to fourth ranks, respectively. Also, the results of the resiliency, and vulnerability indices of the reservoir operation showed that MVGA-MCS and MVGA models have better performance than other models.

     

Sediment flux from Lesser Zab River in Dokan Reservoir: Implications for the sustainability of long‐term water resources in Iraq

Prudent management of Iraqi water resources under climate change conditions requires plans to be based on actual figures of the storage capacity of existing reservoirs. With the absence of sediment flushing measures, the actual storage capacity of Dokan Reservoir (operated since 1959) has been affected by the amount of sediment delivered during its operational life leading to an undetermined reduction in its storage capacity. In consequence, there has not been an update on the dam's operational storage capacity curves. In this research, new operational curves were established for the reservoir based on a recent bathymetric survey undertaken in 2014. The reduction in reservoir capacity during the period between 1959 and 2014 was calculated by the mean of the difference between the designed storage capacity and the storage capacity which was concluded from the 2014 bathymetric survey. Moreover, the rate of sediment transported to the reservoir was calculated based on the overall quantities of accumulated sediment and the water discharge of the Lesser Zab River into the reservoir. The results indicate that the dam capacity is reduced by 25% due to sedimentation of an estimated volume of 367 million cubic metres at water level 480 m.a.s.l. The annual sedimentation rate was about 6.6 million cubic metres, and the sediment yield was estimated to be 701.2 t?km^?3?year.     

三峡水库正常运行期入库流量计算方案分析

总结了三峡水库正常运行期的坝前水位一般控制规律,阐述了三峡库区动库容对其入库流量计算的影响.根据三峡水库的调节性能和坝前水位控制规律,将水库的坝前蓄水状态分为3个等级,并分析了各蓄水等级下的入库流量最佳计算方案,有效解决了入库流量的锯齿跳变问题,符合实际.     

An Interactive Management System for Operational Control of Kirazdere Reservoir (Turkey)

This article presents a prototype, user-interactive computing system for the operational management of the Kirazdere reservoir in Turkey. The aim is to make best use of the full storage capacity of the reservoir for meeting the contractual water-supply obligations as consistently as possible, having regard to the possible risk of downstream flooding. In determining the amount to be released for supply purposes in any one month, the system takes account of the current storage level and predicted inflow. In doing so, the system incorporates the prevailing situation with water-release rules previously derived using a combination of optimisation and simulation-based scenarios analyses, thereby providing a comprehensive analytical capability which is easy to manipulate. For each month, the system provides the operator with a proposed release schedule as well as the opportunity to explore the consequences of alternatives, in terms of the reservoir performance criteria. An important feature of the system is the ability to quickly evaluate a priori, the impacts of different release decisions over an extended period of time for a variety of possible inflow scenarios, including extreme drought and flood periods, helping the operator to establish the robustness of a particular operating policy. Whilst the system has been specifically designed to support the operation of the Kirazdere reservoir, its extension to include a more general class of reservoir management problems would be comparatively simple.