基于模拟-优化模式的供水水库群联合调度规则研究

提出了基于模拟-优化模式的混联供水水库群联合优化调度规则求解框架。首先,通过构建虚拟聚合水库,编制联合调度图,以做出水库群对各用水户的供水方案;其次,通过优化成员水库供水任务分配因子,并结合供水水库群常规调度规则,实现共同供水任务在水库间的优化分配。采用改进粒子群算法 （NSPSO） 对观音阁-葠窝-汤河水库群联合供水调度模型决策变量 （联合调度图调度线位置和成员水库供水任务分配因子） 进行多目标优化,分析联合供水调度过程中目标之间的竞争关系,检验联合调度规则的合理性与有效性以及NSPSO算法的优化效率。     

基于模拟-优化模式的供水水库群联合调度规则研究

提出了基于模拟-优化模式的混联供水水库群联合优化调度规则求解框架。首先，通过构建虚拟聚合水库，编制联合调度图，以做出水库群对各用水户的供水方案；其次，通过优化成员水库供水任务分配因子，并结合供水水库群常规调度规则，实现共同供水任务在水库间的优化分配。采用NSPSO算法对观音阁-葠窝-汤河水库群联合供水调度模型决策变量（联合调度图调度线位置和成员水库供水任务分配因子）进行多目标优化，分析联合供水调度过程中目标之间的竞争关系，检验联合调度规则的合理性与有效性以及NSPSO算法的优化效率。     

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.     

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。     

Multi-Objective Simulation-Optimization Model for Long-term Reservoir Operation using Piecewise Linear Hedging Rule

An efficiently parameterized and appropriately structured piecewise linear hedging rule is formulated and included within a multi-objective simulation-optimization (S-O) framework that seeks to obtain Pareto-optimal solutions for the long-term hedged operation of a single water supply reservoir. Two conflicting objectives, namely, “minimize the total shortage ratio” and “minimize the maximum shortage” are considered in the S-O framework, while explicit specification of constraints is avoided in the optimization module. Evolutionary search based non-dominated sorting genetic algorithm is used as the driver, which is linked to the simulation engine that invokes the piecewise linear hedging rule within the S-O framework. Preconditioning of the multi-objective stochastic search of the time-varying piecewise linear hedging model is effected by feeding initial feasible solutions sampled from the Pareto-optimal front of a simple constant hedging parameter model, which has resulted in significant improvement of the Pareto-optimality and the computational efficiency.

     

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.     

PA-DDS算法在水库多目标优化调度中的应用

Pareto存档动态维度搜索（Pareto-Archived Dynamically Dimensioned Search,PA-DDS）算法是一种求解多目标问题的随机搜索启发式算法。本文将PA-DDS算法引入考虑供水和发电的多目标优化模型优化水库调度图,与非支配排序遗传算法（NSGA-II）和多目标粒子群算法（MOPSO）对比了收敛性,并在求得非劣解分布的均匀性和与理论Pareto前端的相似性方面与NSGA-II进行比较,分析该算法求解水库多目标调度问题的优化性能,对比分析不同目标下的优化调度图。结果表明：PA-DDS算法能够得到更高质量的非劣解集,优化调度图与原设计调度图相比,能更有效协调供水和发电的矛盾,在小幅降低（0.96%）发电量的前提下显著提高（8.07%）水库供水量,平均每年增加经济效益0.55亿元。     

跨流域水库群最优调供水过程耦合研究

为了有效描述和求解跨流域水库群最优调供水过程,本文建立了基于0-1规划方法的水库群最优化调度模型,统一考虑并最终确定了最优调供水过程。为减少模型单次求解的变量数目,同时增加算法全局搜索的能力,本文借用逐步优化算法思想,对传统粒子群进行改进,提出了逐步优化粒子群算法(PRA-PSO)对模型进行求解。最后,通过中国北方某大型跨流域调水工程的实例研究分析了模型的合理性和有效性。最优调供水过程的确定不仅可为采用隐随机优化方法确定跨流域水库群调水规则和供水规则提供最优化样本过程,而且对跨流域调水工程调度运行评价具有重要意义。     

跨流域水库群最优调供水过程耦合研究

为了有效描述和求解跨流域水库群最优调供水过程,本文建立了基于0-1规划方法的水库群最优化调度模型,统一考虑并最终确定了最优调供水过程。为减少模型单次求解的变量数目,同时增加算法全局搜索的能力,本文借用逐步优化算法的思想,对传统粒子群进行改进,提出了逐步优化粒子群算法（PRA-PSO）对模型进行求解。最后,通过中国北方某大型跨流域调水工程的实例研究分析了模型的合理性和有效性。最优调供水过程的确定不仅可为采用隐随机优化方法确定跨流域水库群调水规则和供水规则提供最优化样本过程,而且对跨流域调水工程调度运行评价具有重要意义。     

Scenario Optimisation of Pumping Schedules in a Complex Water Supply System Considering a Cost–Risk Balancing Approach

The optimisation of water pumping plant activation schedules is a significant issue when managing emergency and costly water transfer under a drought risk. This problem needs specific optimisation tools to deal with complex multi-reservoir supply systems and to consider different alternative scenarios. The effectiveness of emergency transfers alleviating droughts requires early warning and activation; on the other hand, the high operating costs of pump stations require system managers to take a robust approach that defines activation rules. The proposed optimisation procedure combines scenario optimisation analysis with a cost-risk balancing approach. The model searches for the identification of optimal decision rules by balancing the risk of water shortages and the operating costs of pumping stations. Scenario optimisation provides ‘barycentric’ values that define the activation threshold by comparing hydrological synthetic series results. A multi-objective approach is also required in order to balance energy cost minimisation requirements and a reduction of damage needs that can be caused by water shortages. Consequently, a scenario optimisation has been developed considering the multi-objective and cost-risk balancing problem. A model application has been developed optimising water management and energy costs in a real water system with shortage risks in the South Sardinia (Italy) region.     

Optimal Allocation of Flood Control Capacity for Multi-Reservoir Systems Using Multi-Objective Optimization Approach

Operation of multi-reservoir systems during flood periods is of great importance in the field of water resources management. This paper proposes a multi-objective optimization model with new formulation for optimal operation of multi-reservoir systems. In this model, the release rate and the flood control capacity of each reservoir is considered as decision variable and the resulting nonlinear non-convex multi-objective optimization problem is solved with ε-constraint method through the mixed integer linear programming (MILP). Objective functions of the model are minimizing the flood damage at downstream sites and the loss of hydropower generation. The developed model is used to determine optimal operating strategies for Karkheh multi-reservoir system in southwestern Iran. For this purpose, the model is executed in two scenarios based on “two-reservoir” and “six-reservoir” systems and for floods with return periods of 25 and 50 years. The results show that in two-reservoir system, flood damage is at least about 114 million dollars and cannot be mitigated any further no matter how hydropower generation is managed. But, in the case of developing all six reservoirs, optimal strategies of coordinated operation can mitigate and even fully prevent flood damage.     

耦合出力破坏深度与弃电准则的梯级水风光互补调度规则研究

梯级水电调度规则是指导控制型水库发电蓄放水的重要依据。随机、波动、间歇性新能源的接入改变了梯级水电运行边界，增加了缺电、弃电风险，导致仅考虑径流季节性波动的调度规则不再适用。依托贵州某梯级水风光综合基地实际工程，剖析了导致缺电、弃电的因素，并从规则形式和模型构建角度给出解决方案。在标准调度规则的基础上，结合对冲规则、满蓄规则，并考虑输电通道容量限制与新能源消纳规则，提出梯级水风光六段式互补调度规则，以减少缺电、弃电;提出出力破坏深度指标度量缺电风险、提出弃电准则避免非必要弃电，并以规则参数为决策变量构建多目标参数模拟优化模型;采用目标优先级非支配排序遗传算法优化规则参数。设置多种新能源装机容量场景、输电通道容量场景和对比规则，从多角度验证本文方法的有效性。结果表明，本文方法能够显著降低梯级水风光综合基地缺电、弃电风险，提高发电量，其中出力破坏深度指标使缺电程度平均降低36.04%、弃电准则使弃电平均减少7.96%。最后，绘制更加简明、直观的梯级水风光互补调度图，以便于实际应用。     

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.     

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.     

A Novel Optimization Method for Multi-Reservoir Operation Policy Derivation in Complex Inter-Basin Water Transfer System

Joint operation of multiple reservoir system in inter-basin water transfer-supply project is a complex problem because of the complicated structure and cooperated operation policy. The combination of high-dimensional, multi-peak and multiple constraints makes it incredibly difficult to obtain the optimal rule curves for multi-reservoir operation. In view of this, we constructed a joint optimization operation model, considering both water supply and transfer, and proposed the concept of “shape constraints”. To obtain the solution of this high-dimensional optimization model, a novel progressive optimum seeking method, namely Progressive Reservoir Algorithm-Particle Swarm Optimization (PRA-PSO), is presented based on the nature of progressive optimization algorithm (POA) and standard particle swarm optimization (PSO). The water transfer project in northeast China, consisting of three routes eight reservoirs, is selected as a case study. The results show that (1) PRA-PSO is yielding much more promising results when compared with other optimization techniques; (2) shape constraints would narrow the scope of feasible solution area but increase the convergence of algorithm; (3) because of the strong interaction between water transfer and water supply action, the progressive setting of PRA-PSO should be in accordance with the order of reservoir water transfer. The case study indicates the novel optimization method could effectively increase the chance of jumping out of local optimal points, thereby searching for better solutions.     

引江济淮工程（河南段）多目标水量优化调度

引江济淮工程（河南段）涉及河道、闸泵、管道和调蓄水库,约束条件复杂,常规的优化调度算法难以搜索可行解,求解效率低。选用受水区缺水率平均值最小、泵站总抽水量最小和受水区缺水率标准差最小作为目标函数,从供水保障、供水成本和公平性角度构建多目标水量优化调度模型。基于可行搜索思路,结合逆序演算和顺序演算过程对约束条件进行处理,引入决策系数,通过映射关系使搜索空间保持在可行域中,结合多目标非支配排序遗传算法（non-dominated sorting genetic algorithms,NSGA-II）进行求解,得到Pareto最优解集,并采用熵权法进行方案优选。结果表明,基于可行搜索的NSGA-II算法能够有效求解复杂调度系统的多目标优化问题,综合考虑多个目标的最优方案相对单目标方案更加合理,结果可为引江济淮工程（河南段）运行管理提供决策支撑。     

基于决策因子选择的梯级水库多目标优化调度规则研究

运用极端随机森林挖掘水库调度信息,考虑各水库相关因子与决策目标的相互关系,提出了梯级水库输入数据选择(Cascade-reservoir Input-variables Selection,CIS)方法,引入Gaussian径向基函数建立水库调度规则,并采用PA-DDS多目标算法对水库调度规则参数进行优化,得到了同时考虑供水和发电的多目标优化调度规则集。汉江上游梯级水库的应用结果表明:CIS方法能优选得到较为稳定的决策因子,且能在充分利用已有优选信息的同时避免决策因子选取上的重复和冗余;经梯级多目标优化调度,优选的决策因子能得到比传统决策因子结果分布更优的非劣解集,在以发电为主要目标进行优化调度时,能有效调整汛期和非汛期的水量利用方式,梯级水库年均发电量和供水量分别提高了0.33%和7.84%。     

Multi-Objective Optimization of the Reservoir System Operation by Using the Hedging Policy

In the present study the WEAP-NSGA-II coupling model was developed in order to apply the hedging policy in a two-reservoir system, including Gavoshan and Shohada dams, located in the west of Iran. For this purpose after adjusting the input files of WEAP model, it was calibrated and verified for a statistical period of 4 and 2 years respectively (2008 till 2013). Then periods of water shortage were simulated for the next 20 years by defining a reference scenario and applying the operation policy based on the current situation. Finally, the water released from reservoirs was optimized based on the hedging policy and was compared with the reference scenario in coupled models. To ensure the superiority of the proposed method, its results was compared with the results of two well-known multi-objective algorithms called PESA-II and SPEA-II. Results show that NSGA-II algorithm is able to generate a better Pareto front in terms of minimizing the objective functions in compare with PESA-II and SPEA-II algorithms. An improvement of about 20% in the demand site coverage reliability of the optimum scenario was obtained in comparison with the reference scenario for the months with a higher water shortage. In addition, considering the hedging policy, the demand site coverage in the critical months increased about 35% in compared with the reference scenario.     

Coupled Operating Rules for Optimal Operation of Multi-Reservoir Systems

Due to the complexity of multi-reservoir system operation problems, researchers usually prefer to assume lumped demands located downstream of such systems. Consequently, distributed local demands through the system are neglected or supplied completely (e.g. using Standard operating policy, SOP), in order to simplify the problem. In this study, Coupled Operating Rules (COR) as a simple and suitable operating policy is applied for optimal operation of multi-reservoir systems with local demands. The applied policy includes two types of linear rules, which are defined to determine total releases and local water allocations in decision points. This policy is adopted within a simulation-optimization approach to optimally operate a three-reservoir system in the Karkheh river basin. Obtained results indicate that the proposed strategy reduces the intensity of demand deficits and distributes the occurred shortages throughout the system properly. Moreover, the system losses are managed appropriately and big unbalanced local shortages are prevented. Although COR strategy decreases the reliability of local demands compared to SOP, it is a reasonable operating policy for systems with distributed local demand sites. Moreover, in this study an effective Improved Melody Search (IMeS) algorithm is proposed to achieve the optimum values of operating rules’ parameters. The efficiency of the optimization method is compared to the results achieved by other selected well-known heuristic search methods. Based on the experimental results, it is revealed that the proposed algorithm is more effective in finding precise solutions over a long-term period, comparing with the other conventional algorithms.     

Multi-Objective Differential Evolution for Design of Cascade Hydropower Reservoir Systems

After Paris Agreement and obligation made by various countries to decrease greenhouse gases, generation of clean energy with low carbon was taken into consideration. Hydropower plant is considered as a clean, cheap and renewable energy source for generating electrical energy. Through the construction of the multipurpose dams and their optimal planning and management, we may decrease the potential losses sustained by aquatic ecosystem in addition to supplying the energy and fulfilling the industrial, agricultural and drinking water demands. In the present study, a multi-objective optimization model was proposed for determination of design parameters in cascade hydropower multi-purpose reservoir systems. Considering the significant number of constraints and decision variables and non-convex form of the objective functions and constraints, particularly in multi-reservoir systems, a multi-objective evolutionary algorithm (MOEA) known as non-dominated sorting differential evolution (NSDE) was developed to solve the problem and reduce the computational costs. Karkheh River basin was selected as a case study in order to make an assessment on the capabilities and strength of the model. This basin is capable of generating hydropower energy and agricultural development with high environmental considerations due to Hurolazim International Wetland. Based on the results, we may supply various demands such as environmental demands of the aquatic ecosystem with high reliability as well as generating firm hydropower energy through optimal design of cascade hydropower reservoirs.