A real-time operation optimization model for flood management in river-reservoir systems

In this paper, a new methodology has been developed for real-time flood management in river-reservoir systems. This methodology is based upon combining a Genetic Algorithm (GA) reservoir operation optimization model for a cascade of two reservoirs, a hydraulic-based flood routing simulation model in downstream river system, a Geographical Information System (GIS) based database, and application of K-Nearest Neighbor (K-NN) algorithm for development of optimal operating rules. The GA optimization model estimates the optimal hourly reservoirs’ releases to minimize the flood damages in the downstream river. GIS tools have also been used for specifying different land-uses and damage functions in the downstream floodplain and it has been linked to the unsteady module of HEC-RAS flood routing model using Hec-GeoRAS module. An innovative approach has also been developed using K-NN algorithm to formulate the optimal operating rules for a system of two cascade reservoirs based on optimal releases obtained from the optimization model. During a flood event, the K-NN algorithm searches through the historical flood hydrographs and optimal reservoir storages determined by the optimization model to find similar situations. The similarity between the hydrographs is quantified based on the slopes of rising and falling limbs of inflow hydrographs and reservoir storages at the beginning of each hourly time step during the flood events for two cascade reservoirs. The developed methodology have been applied to the Bakhtiari and Dez River-Reservoir systems in southwest of Iran. The results show that the proposed models can be effectively used for flood management and real-time operation of cascade river-reservoir systems.     

基于优化-模拟技术的生态库容

为发挥水库在水资源开发利用与河流生态环境问题之间的协调作用,以丹江口水库为例,探讨了综合利用水库生态库容划分方法。以丹江口水库下游襄阳和仙桃为控制断面,采用Tennant法计算下游河道生态流量的参考值。在考虑丹江口水库的防洪、生态、供水、调水、发电、航运等综合任务和汉江中下游水量联系的基础上,建立了综合利用水库的生态库容优化模型,拟定了4组调度规则,应用自适应遗传算法和模拟调度方法进行求解。计算结果表明:设置生态库容后的调度图能较好地满足控制断面对生态流量的需求,获得较佳综合利用效益。     

基于多目标遗传算法的巨型水库群发电优化调度

低碳时代,水电作为清洁可再生能源,节能发电调度为梯级水电联合调度运行带来了难得的历史机遇,如何有效地开展梯级水库群优化调度,充分合理利用水能资源,是流域梯级电站管理迫切需要解决的问题。文章在对清江梯级与三峡梯级径流特征分析的基础上,建立了以水库群整体发电量最大和弃能最小为目标的梯级调度模型。根据电力系统对三峡、葛洲坝、水布垭、隔河岩、高坝洲水电站的要求,用1951—2002年的月径流资料和典型年的日径流资料进行长期和短期优化调度,采用多目标遗传算法得到清江3个电站、三峡-葛洲坝2电站单独运行和联合优化调度发电指标,5库联合优化调度系统多年平均发电量增加约21亿kW.h;短期(日)优化调度较长期(月时间尺度)优化调度发电效益有进一步提升,增发电量约9.68亿kW.h。研究表明,充分利用清江和三峡梯级实际运行位置相近、水力联系紧密、互补性强的特点,统一安排电站机组运行模式,合理分配机组出力,可在来水量相同的条件下获得更大的效益。     

Optimal water and waste load allocation in reservoir–river systems: a case study

In this paper, a new methodology is developed for optimization of water and waste load allocation in reservoir–river systems considering the existing uncertainties in reservoir inflow, waste loads and water demands. A stochastic dynamic programming (SDP) model is used to optimize reservoir operation considering the inflow uncertainty, and another model called PSO-SA is developed and linked with the SDP model for optimizing water and waste load allocation in downstream river. In the PSO-SA model, a particle swarm optimization technique with a dynamic penalty function for handling the constraints is used to optimize water and waste load allocation policies. Also, a simulated annealing technique is utilized for determining the upper and lower bounds of constraints and objective function considering the existing uncertainties. As the proposed water and waste load allocation model has a considerable run-time, some powerful soft computing techniques, namely, Regression tree Induction (named M5P), fuzzy K-nearest neighbor, Bayesian network, support vector regression and an adaptive neuro-fuzzy inference system, are trained and validated using the results of the proposed methodology to develop real-time water and waste load allocation rules. To examine the efficiency and applicability of the methodology, it is applied to the Dez reservoir–river system in the south-western part of Iran.     

基于防洪库容总量控制的雅砻江下游梯级水库蓄水策略研究

根据长江防御洪水方案对雅砻江梯级水库的防洪库容预留要求,分析了预留防洪库容对梯级电站蓄水发电的影响。结合雅砻江水电开发的特点,提出了梯级水库防洪库容总量控制的解决思路,建立了基于防洪库容总量控制的蓄水期发电量最大模型,计算分析了9种不同来水情景的梯级水库优化蓄水方案,并给出了梯级水库总体优化蓄水策略。对该类问题研究具有一定借鉴意义。     

跨流域联合供水水库补偿特性研究

跨流域水库补偿特性主要包括水文补偿特性与库容补偿特性两个方面,以大连市两座重要的供水水源碧流河水库、英那河水库为例,运用Copula函数分析了碧流河水库、英那河水库天然入库径流年系列、汛期系列、非汛期系列的丰枯遭遇概率,采用统计学方法分析了两座水库连续枯水系列年的遭遇情况。并建立了考虑外调水源的碧流河、英那河水库联合优化供水调度模型,模拟得出了规划水平年水库供水量与下泄水量,利用两座水库长系列调节历年下泄水量之间的对应关系对水库库容补偿特性进行了分析。研究成果可以为大连市境内水系连通规划提供一定的依据,水库补偿特性研究方法也可为其它类似工程规划提供借鉴。     

水库防洪等蓄量优化调度模型及应用

等蓄量法是中国水库防洪规划与实时调度中常用的调度方式,其3个参数（等蓄流量、起蓄流量和等蓄历时）一直采用试算方法推求。以等蓄流量为输入参数,引入蓄放水0~1状态变量,定义了逐时段水库蓄水量之和最小的线性目标函数,并设置蓄水状态连续性约束解决等蓄历时的推求,建立了水库防洪等蓄量优化调度的0~1整数线性规划模型（RFEV-ILP）。通过亭子口水库应用表明,该模型算法稳定,与理想补偿调度方式计算的防洪库容相差不足1%。该优化模型不仅可以推求防洪库容、起蓄流量及等蓄历时与等蓄流量之间的数值关系,而且能较好地揭示防洪风险与等蓄流量之间的关系、防洪控制点距离水库的远近对等蓄流量可选范围及相应采取防洪策略的影响。     

基于微分对策理论的多沙河流水库调度

水库的排沙问题一直是多沙河流水库调度研究的重点之一。由于大部分多沙河流的来水来沙主要集中于汛期,因此水库汛期的蓄水兴利与泄水排沙的矛盾十分突出,具有典型的博弈关系,该关系可以利用博弈的相关理论进行描述。基于微分对策理论,将多沙河流水库汛期的供水兴利与泄水排沙看作博弈的双方,建立起以排沙和供水的综合效益作为性能指标函数的多沙河流水库汛期调度模型,研究了多沙河流水库汛期的调度问题,并通过陕西黑河某水库的实测资料对该模型进行了验证计算。计算结果表明,建立的调度模型能够较好地反映多沙河流水库汛期调度中的主要矛盾,实现对供水与排沙综合效益的优化。     

Integral equation solution for three-dimensional heat transfer in multiple-fracture enhanced geothermal reservoirs

For the prediction of energy production from multiple-fractured geothermal reservoirs, previous models basically focused on the one-dimensional conduction in the rock containing evenly distributed fractures of equal scale. Here, a novel model is described to numerically investigate the three-dimensional heat transfer in geothermal reservoirs with unevenly spaced disc fractures of various sizes including the aperture and radius. In terms of the water flow through each fracture, an approximate analytical solution is obtained on the assumption that the water pressure disturbances, induced by the fracture margin and extraction (injection) operation, at the injection (extraction) well center and at different locations within the injection (extraction) well range were approximately equal. By the integral equation scheme for two-dimensional planar fractures, the three-dimensional problem of heat exchange is simulated without the reservoir discretization. The singular integral is analytically calculated in polar coordinates whereas the nonsingular integrand is numerically estimated by the Gaussian quadrature method in Cartesian coordinates. Compared with the one-dimensional simplification, the three-dimensional heat conduction remarkably alters the prediction of extraction temperature. In addition, the reservoir temperature field is also significantly influenced by the spacings and dimensions of fractures. The present model may be used for the estimation, design, and optimization of a geothermal reservoir.     

基于RAGA的供水库群水资源配置模型研究

针对动态规划在供水库群优化调度中存在"维数灾",且难以获得真正最优解这一缺点,将改进的加速遗传算法应用到供水库群的水资源优化配置之中。在加速遗传算法中,嵌入局部搜索,以加强算法的全局寻优能力。以库群间的水利联系为线索,设计了相应的算法框架,并提出了供水策略区间的概念。为了体现该算法的优越性,以二个串联供水水库的水资源优化配置为例,选用该方法与基于动态规划的轮库迭代法进行比较研究。结果表明该方法合理可行、收敛速度快,有一定的实用性。     

东江三大水库联合调度下惠州河段水温变化响应研究

以东江流域控制站点博罗站为代表,通过构建一维水流水温模型,计算分析了东江三大水库不同出库流量对下游惠州河段水温的影响,探讨了该地区基于水温的鱼类生态调度目标,提出了东江三大水库3月份的水库联合生态调度方案.研究结果表明,在东江三大水库出库流量比例不变的情况下,博罗站3月份水温随着流量的增大而增大,但变化并不明显;在博罗站流量不变的情况下,东江三大水库出库流量的变化对博罗站水温有较大的影响,其中以白盆珠水库的影响最为显著.结合前人的研究成果认为,在博罗站流量320m3/s的情况下,保持白盆珠水库3月份最小出库流量为30m3/s,有利于东江下游惠州河段的生态条件改善.     

小浪底水库“腾库迎洪”期异重流形成分析

小浪底水库异重流的形成与运行规律是关系黄河调水调沙方案拟定的重要指标。基于现场调研、理论探讨与预测分析结合等手段,明晰了2018年"腾库迎洪"期小浪底水库来水来沙过程,根据水库调度与库区淤积形态等边界条件,观测了异重流的形成与运行,采用基于流速分布的水库异重流潜入点预测公式进行了计算分析。结果表明:2018年7月库区产生的剧烈冲刷,在潜入点处发生大量淤积,水深大幅减小,引起潜入点下移;潜入点位置随入库水沙增大、坝前水位降低及库区淤积的推进向坝前移动,计算与实测结果反映了该变化过程。     

水库水体生态系统数值模拟模型及其应用──以丹江口水库为例

介绍了水库生态系统模拟模型,对水库生态变化过程及其数学模拟方法进行了分析.采用1995年的水文、气象、水库调度资料、入库河流水质及水库初始水质资料模拟了该年度丹江口水库水体生态逐日变化过程.     

小浪底水库“腾库迎洪”期异重流形成分析

小浪底水库异重流的形成与运行规律是关系黄河调水调沙方案拟定的重要指标。基于现场调研、理论探讨与预测分析结合等手段,明晰了2018年“腾库迎洪”期小浪底水库来水来沙过程,根据水库调度与库区淤积形态等边界条件,观测了异重流的形成与运行,采用基于流速分布的水库异重流潜入点预测公式进行了计算分析。结果表明:2018年7月库区产生的剧烈冲刷,在潜入点处发生大量淤积,水深大幅减小,引起潜入点下移;潜入点位置随入库水沙增大、坝前水位降低及库区淤积的推进向坝前移动,计算与实测结果反映了该变化过程。     

雅砻江下游梯级水库生态友好型优化调度

根据雅砻江下游梯级水库水电站的布置和河道生态环境要求,分别设置了两个流量控制断面:锦屏二级电站引水闸址下减水河段、二滩电站坝址下游河段.针对这两个控制断面河道流量的要求,提出了25组生态流量控泄方案,建立了以梯级水电站群发电量最大为目标的长期优化调度模型,并采用动态规划法进行求解,获得各个方案下梯级水电站群多年平均发电量及水库调度出流过程.比较分析了减水河段生态流量及二滩水库泄流控制方案对发电量的影响,定义并计算了生态需水电能损失指标.对梯级水库调度出流过程进行了初步评价.结果表明:二滩水库出流维持天然径流模式,将限制水库调节能力和减少梯级电站发电效益.     

基于GIS的黄水河地下水库实时调度管理系统与数值模拟研究

建设地下水库是我国北方特别是沿海地区解决水资源短缺的有效途径之一。本文依据龙口市黄水河地下水库的运行管理需要，建立了基于GIS的地下水库实时调度管理信息系统及数值模拟模型。对地下水库进行了调蓄调控模拟计算．为地下水库制定合理的调度运行管理方案和补源工程规划提供了科学依据。     

Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA–GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years’ worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA–GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA–ANN models. The results indicate that the SARIMA–GEP model (R ²=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA–ANN (R ²=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA–GEP over the SARIMA–ANN model.     

耦合水库群参数化方案的区域陆面水文模拟

中国水库数目众多,密集的水库运行和调蓄影响着陆地水循环和陆气间的水分能量交换过程,给高强度开发地区水文规律认知和水文模拟及预报带来了挑战。围绕这一问题,本研究以鄱阳湖流域及流域内千余座水库为研究对象,从水库水量平衡方程、水库蓄泄规则、多阻断扩散波汇流等方面构建了水库群参数化方案,并从地表水、地下水、蒸散发、能量通量等角度实现了其与陆面水文双向耦合模式（CLHMS）的动态耦合。结果表明:所构建的水库群参数化方案可以较好地模拟水库的蓄泄过程,提高了耦合模式在鄱阳湖流域的径流模拟精度;水库群可以使赣江、信江、抚河丰水期径流减少3.7%~6.0%,枯水期径流增加5.9%~12.6%,多年平均径流减少0.6%~1.5%;在空间分布上,水库群对流域中部和北部径流的调蓄作用相对显著。本研究所改进的陆面水文模式可以为高强度人类活动影响下气象、水文、水资源交叉领域的研究提供分析工具和模型基础,从而支撑变化环境下区域水资源的可持续利用。     

应对干旱的黄河干流梯级水库群协同调度

科学控制梯级水库蓄泄过程是减少旱灾损失的重要手段。以减少干旱年份流域缺水量和优化缺水时空分布为目标,构建应对干旱的梯级水库群多时空尺度协同优化调度模型。采用交互式与改进粒子群优化方法,外层寻求多年调节水库旱限水位最优控制,内层优化梯级水库群年内蓄泄过程,实现流域水资源年际调控、年内优化、库群协同、空间协调。以2014年的黄河流域重旱为例,通过模型优化提出2012—2014年龙羊峡水库旱限水位及梯级水库群年内蓄泄过程,结果表明:通过龙羊峡水库旱限水位控制实现跨年度补水,控制各年度缺水率在4.9%~5.7%之间,通过水库群出库过程优化控制不同区域各时段缺水均匀分布,将农业缺水率控制在7.0%~11.0%之间,显著减轻了旱灾损失。     

应对干旱的黄河干流梯级水库群协同调度

科学控制梯级水库蓄泄过程是减少旱灾损失的重要手段。以减少干旱年份流域缺水量和优化缺水时空分布为目标,构建应对干旱的梯级水库群多时空尺度协同优化调度模型。采用交互式与改进粒子群优化方法,外层寻求多年调节水库旱限水位最优控制,内层优化梯级水库群年内蓄泄过程,实现流域水资源年际调控、年内优化、库群协同、空间协调。以2014年的黄河流域重旱为例,通过模型优化提出2012—2014年龙羊峡水库旱限水位及梯级水库群年内蓄泄过程,结果表明:通过龙羊峡水库旱限水位控制实现跨年度补水,控制各年度缺水率在4.9%~5.7%之间,通过水库群出库过程优化控制不同区域各时段缺水均匀分布,将农业缺水率控制在7.0%~11.0%之间,显著减轻了旱灾损失。