Hydropower Optimization for the Lower Seyhan System in Turkey using Dynamic Programming

Abstract

Dynamic programming with successive approximation has been used in the past for optimizing multi-reservoir water resources systems. In this study, the State Incremental Dynamic Programming (SIDP) model is developed for energy optimization of multi-reservoir systems. A random file access method is used for reaching initial and intermediate data to cope with the curse of dimensionality of dynamic programming. A conventional dynamic programming method is used for each single reservoir to find the initial trajectory of the reservoirs. Then, the computer program developed in the study is applied to the multipurpose-multi-reservoir system in Lower Seyhan Basin, which has six reservoirs, some of which are serial and some parallel. First, extended historical flows were used to maximize firm energy in the critical period, and then total energy in the total flows. The program was run with 50-year long segments (20 flow scenarios) of the synthetic flow data generated by using the HEC-4 generalized computer program to take into account the stochastic nature of stream flows. An increment of approximately 20 percent in total energy was obtained by using the model for the Lower Seyhan System, as compared to that calculated previously by conventional methods.     

混沌蚁群算法在水库优化调度中的应用

提出一种基于混沌优化算法和蚁群算法相结合的混合算法,在求解水库优化调度问题的方法。根据混沌变量的随机性和遍历性,利用混沌变量进行优化搜索,从而有效地克服了蚁群算法存在的效率低、易于演化停滞及陷入局部最优等问题。又利用蚁群算法信息素正反馈的优点,改善了混沌搜索的盲目性,提高了搜索的效率。通过实例计算,结果表明该算法具有效率高及较强的全局寻优能力。     

水电站水库群长期运行优化模型和应用

水电站水库群长期运行优化模型及其应用,是根据系统工程的思想,应用线性规划的方法建立起来的.它可进行梯级水电站水库群和跨流域水电站水库群的长期运行的优化.应用这一模型和方法,可大幅度提高水电站 '群的发电效益.     

蜜蜂进化型遗传算法在水库优化调度中的应用

提出了一种基于蜜蜂进化型遗传算法的水库优化调度问题的求解方法,并通过实例对蜜蜂进化型遗传算法和标准遗传算法的性能做了比较.结果表明,在进化代数相同的条件下,由于蜜蜂进化型遗传算法在配种选择算子上使用种群的最优个体作为蜂王,提高了种群收敛速度;再者,在代进化过程中引入一个随机种群,保持了群体的多样性,提高了算法的勘测能力.     

Optimal Reservoir Operation Using Multi-Objective Evolutionary Algorithm

This paper presents a Multi-objective Evolutionary Algorithm (MOEA) to derive a set of optimal operation policies for a multipurpose reservoir system. One of the main goals in multi-objective optimization is to find a set of well distributed optimal solutions along the Pareto front. Classical optimization methods often fail in attaining a good Pareto front. To overcome the drawbacks faced by the classical methods for Multi-objective Optimization Problems (MOOP), this study employs a population based search evolutionary algorithm namely Multi-objective Genetic Algorithm (MOGA) to generate a Pareto optimal set. The MOGA approach is applied to a realistic reservoir system, namely Bhadra Reservoir system, in India. The reservoir serves multiple purposes irrigation, hydropower generation and downstream water quality requirements. The results obtained using the proposed evolutionary algorithm is able to offer many alternative policies for the reservoir operator, giving flexibility to choose the best out of them. This study demonstrates the usefulness of MOGA for a real life multi-objective optimization problem.     

水库多目标优化调度技术比较研究

多目标智能优化算法种类繁多,不断涌现,在水库优化调度中得到了广泛应用,但多目标智能优化技术仍然是目前水库群综合利用优化调度研究中的热点和难点之一。已有的研究算法大多是关于水库优化调度中适用性的应用研究,且实际问题简化多,在算法算子的选择、算法性能的探讨和比较、特别是多目标优化等方面还不够深入。为此,选择应用较为广泛的NSGA-Ⅱ和DEMO算法,从变量规模、约束处理技术等方面,对其在水库多目标优化调度中的应用效果进行初步分析、比较和评估,为水库多目标优化调度算法的选择提供了参考。     

Application of a Genetic Algorithm for the Optimization of a Complex Reservoir System in Tunisia

A genetic algorithm (GA) model is developed and used for optimizing the allocation of water resources within a complex multiple reservoir system located in Tunisia. The GA model considers two objectives: the water allocation to demand centers and the salinity level of the water supply to end users. These two objectives are combined into a single objective function using a weighting factor approach. Five different cases (representing five different weighting factor combinations) were analyzed by the GA model to produce the “optimum” allocation of water resources for each case. The generated solutions exhibited low variability. The results are then compared using a range of system performance indicators to measure reliability, resilience, and vulnerability. The evaluation of the system performance is an essential step to help system managers identify the preferred allocation strategy and it provides a comprehensive insight into system behavior.     

Application of the Shuffled Frog Leaping Algorithm for the Optimization of a General Large-Scale Water Supply System

A water supply system is a complex network of pipes, canals and storage and treatment facilities that collects, treats, stores, and distributes water to consumers. Increasing population and its associated demands requires systems to be expanded and adapted over time to provide a sustainable water supply. Comprehensive design tools are needed to assist managers determine how to plan for future growth. In this study, a general large-scale water supply system model was developed to minimize the total system cost by integrating a mathematical supply system representation and applying an improved shuffled frog leaping algorithm optimization scheme (SFLA). The developed model was applied to two hypothetical water communities. The operational strategies and the capacities for the system components including water transport and treatment facilities are model decision variables. An explicit representation of energy consumption cost for the transporting water in the model assists in determining the efficacy of satellite wastewater treatment facilities. Although the water supply systems studied contained highly nonlinear terms in the formulation as well as several hundred decisions variables, the stochastic search algorithm, SFLA, successfully found solutions that satisfied all the constraints for the studied networks.     

Effect of Averaging Operators in Fuzzy Optimization of Reservoir Operation

Fuzzy multiobjective decision makingmodels generally rely on the aggregation of theobjectives to form a decision function. The generalizedaveraging operator is usually adopted for aggregatingmultiple and unequal objectives because it allows trade-off amongst the objectives, and has been shown to besuitable to model human decision making behavior. In thefield of water resource management, most of the decision-making problems involving the generalized averagingoperator implicitly assume the decision maker (DM) israther optimistic. The analysis of the DM's behaviorduring the aggregation process and its impact on theperformance of the system, has therefore never beenaddressed by many researchers and decision makers. Theaim of this paper is to investigate the relationshipbetween decision makers' index of optimism and the long-term performance of a reservoir resource. Morespecifically, the generalized averaging operator, whoseparameter can be interpreted as the DM's index ofoptimism, is imbedded into a fuzzy stochastic dynamicprogram (FSDP). This approach is developed andimplemented to derive optimal operating policies for thehydroelectric complex of the Uruguay River basin inSouthern Brazil. FSDP-derived policies with differentindices of optimism are then compared with simulation. Weshow that system performance may be influenced by thedecision maker's behavior during the aggregation, andthat the optimistic assumption may not yield tosatisfactory results, especially during critical timeperiods.     

Multi-Reservoir Operation Planning Using Hybrid Genetic Algorithm and Linear Programming (GA-LP): An Alternative Stochastic Approach

Many models have been suggested to deal with the multi-reservoir operation planning stochastic optimization problem involving decisions on water releases from various reservoirs in different time periods of the year. A new approach using genetic algorithm (GA) and linear programming (LP) is proposed here to determine operational decisions for reservoirs of a hydro system throughout a planning period, with the possibility of considering a variety of equally likely hydrologic sequences representing inflows. This approach permits the evaluation of a reduced number of parameters by GA and operational variables by LP. The proposed algorithm is a stochastic approximation to the hydro system operation problem, with advantages such as simple implementation and the possibility of extracting useful parameters for future operational decisions. Implementation of the method is demonstrated through a small hypothetical hydrothermal system used in literature as an example for stochastic dual dynamic programming (SDDP) method of Pereira and Pinto (Pereira, M. V. F. and Pinto, L. M. V. G.: 1985, Water Res. Res. 21(6), 779–792). The proposed GA-LP approach performed equally well as compared to the SDDP method.     

长江上游水库群多目标优化调度模型及应用研究I：模型原理及求解

水库群调度中发电与供水、生态等目标既非完全对立也非完全协调,其优化调度决策非常复杂.本文以长江上游15座大型水库群联合调度为背景,研究建立了包含发电、河道外供水和河道内生态用水等目标的非线性优化调度模型,以逐步优化算法(POA)为基础,引入优化窗口(L)和滑动距离(l)两个参数,提出了扩展型逐步优比算法(E-POA)以提高非线性模型的求解效率与效能.经与线性全局优化策略相比,E-POA方法有效、解集合理.长江上游15座大型水库长系列联合多目标调度计算结果表明,水库群调度在发电、供水、生态等目标存在不对称博弈关系,河道外供水与河道内生态用水竞争强烈,发电与河道内供水竞争较弱.当优化计算的总发电量为总设计发电量的96.3％时,系统的发电量、河道外供水和河道内生态用水目标可达成较好的协调统一.多年平均条件下,15座水库群联合调度的总期望发电量为2 625.8～2 700.1亿kW·h,略小于总设计发电量.     

基于多目标决策技术的水库优化调度

现代水库承担的功用较多,传统的以单一功用为目标的水库调度已不能适应经济社会的发展。多目标决策在多个矛盾的目标下做出最优的均衡决策,有利于发挥水库综合功用。以水库本年发电量最大和下年水库蓄能最大双目标进行水库优化调度。工程实践证明,运用多目标决策技术进行水库调度可行、正确。     

A Bayesian Stochastic Optimization Model for a Multi-Reservoir Hydropower System

This paper presents the development of an operating policy model for a multi-reservoir system for hydropower generation by addressing forecast uncertainty along with inflow uncertainty. The stochastic optimization tool adopted is the Bayesian Stochastic Dynamic Programming (BSDP), which incorporates a Bayesian approach within the classical Stochastic Dynamic Programming (SDP) formulation. The BSDP model developed in this study considers, the storages of individual reservoirs at the beginning of period t, aggregate inflow to the system during period t and forecast for aggregate inflow to the system for the next time period t + 1, as state variables. The randomness of the inflow is addressed through a posterior flow transition probability, and the uncertainty in flow forecasts is addressed through both the posterior flow transition probability and the predictive probability of forecasts. The system performance measure used in the BSDP model is the square of the deviation of the total power generated from the total firm power committed and the objective function is to minimize the expected value of the system performance measure. The model application is demonstrated through a case study of the Kalinadi Hydroelectric Project (KHEP) Stage I, in Karnataka state, India.     

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.     

改进的遗传算法在水库调度中的应用

为了改善遗传算法在水库优化调度中的应用效果,采用自适应遗传算法和广度变异模块相结合的分层收敛算法:第一层采用广度变异和外部存档的方式改善种群的多样性;第二层嵌套广度变异模块,并采用自适应遗传算法进行全局搜索。通过比较自适应遗传算法和分层进化算法,结果显示:基于遗传算法的分层算法具有高效的全局搜索能力,避免了自适应遗传算法陷入局部最优的缺陷,在一定收敛条件下得到了更接近全局最优的目标值。     

水库群长期优化调度研究

在进行水库群长期优化运行的研究中，讨论了一种适合于寻求水资源系统优化运行决策规则调度模型。该模型包括双状态动态规划（ＢＳＤＰ）和混合回归的疏系数模型。该调度模型充分反映了水库群最优运行的规律，且大大节省了计算时间的内存量。模拟运行结果表明，该模型是可行的。     

PLC在水轮机顶盖排水控制系统中的应用

本文介绍了PLC在黄河万家寨水电站水轮机顶盖排水控制系统中的选型、I/O端子分配、编程方法并进行了应用分析。     

Operating Rules of an Irrigation Purposes Reservoir Using Multi-Objective Optimization

A multi-objective optimization technique for the operation of an irrigation reservoir is presented in this paper. The study deals with two different objective functions (OF): the minimization of reservoir release deficit from the irrigation demand (OF1) and the maximization of net benefit by the demand sector (OF2). In the first step, monthly optimization of each individual objective was performed with a deterministic non-linear programming (NLP) algorithm, that gave the lower and upper bounds for the multi-objective analysis. In the second step, multi-objective optimization was performed through the Constraint method that operates by optimising the objective function OF1, while the other (OF2) was constrained to satisfy release strategies generated by the optimization. Non-dominated set of release strategies is generated by parametrically varying the bounds of the constraints obtained from the individual optimal solutions. In the third step, the interactive analytical Step method was applied to find the best compromise solution, between the two OFs, by minimizing the distance of each non-dominated solution to an ideal solution that represents the utopian optimum for both OF1 and OF2. Furthermore, the interactive approach allows to improve the performance of the reservoir in terms of compromise irrigation releases, by changing the OF values until the satisfaction of predetermined criteria fixed by the planners and decision makers. The proposed water allocation model was applied to the Pozzillo reservoir operation, that supplies the Catania Plain irrigation area (Eastern Sicily).     

水库防洪补源优化模式的探讨与实践

汛期将洪水经水库调蓄后以小流量下泄再回灌补给地下水，是多余洪水利用的一种良好方式，采用动态规划技术，结合水文预报，气象预报资料的使用，探讨了水库防洪，补源的优化调度方法，调度中采用了能同时反映山东省的超渗产流与蓄潢产流的复合产流模型计算入库洪水，在进行产流和汇流计算和的基础上，建立了防洪，补源优化调度模型，文中介绍了利用太河水库调蓄洪水进行回灌的工作实践，并对其经济效益作了计算分析。     

实时水库优化调度决策支持系统及其应用

水库是水库运行管理的中心环节，在水库调度中，将数学模型与专家系统结合使用，建立长中短期套接的实时兴利优化调度、防洪实时优化调度及其辅助模型系统；各模型通过逐时段滚动控制与反馈相结合，可以增加水库调度的效益，减少不确定性因素对调度的影响，并提出用专家系统对优化调度的各个环节进行评价，以尽可能降低优化调度方案的风险，提高优化调度方案的可接受程序，所提出的方法已编编制出使用灵活方便的软件，并经实际使用，