水电站群发电能力的优化方法及应用分析

针对水电站群中长期发电计划编制的调度期末控制水位决策需求,建立以发电能力最大为目标的水电站群联合优化调度模型,并采用改进的逐次逼近与离散微分动态规划组合算法进行求解。以华电贵州区域乌江和北盘江两流域水电站群为例,采用2013年实际来水过程计算,通过与发电量最大、补偿效益最大等传统优化目标对比分析。结果表明:本文模型可根据各电站发电效率变化情况自动确定水库蓄放策略,实现水电站群调度期末控制水位及对应发电计划过程的同步优化,准确体现水电站群调度期内总发电量和调度期末总蓄能量的动态博弈关系。     

水电站长中短期嵌套预报调度耦合实时来水系统动力学建模方法研究及应用

水电站优化调度是水电能源系统优化运行与管理研究领域的关键科学问题,已有水电站优化调度研究较少考虑不同尺度调度模型间的衔接,长、中、短期优化调度相互孤立,彼此之间缺乏耦合机制,在指导水电站实际运行中存在不足。为此,研究建立了水电站长中短期嵌套预报调度模型,并引入系统动力学反馈机制,提出了一种水电站长中短期嵌套耦合实时来水系统动力学预报调度模型。长、中、短期调度模型分层嵌套,中长期预报调度结果作为短期调度的"期望指导过程线",根据水电站预报来水和面临日实时来水存在误差所导致的水位偏差进行实时反馈、动态修正调度决策,从而指导水电站做出更为合理的调度决策。为检验本文模型方法的有效性,研究选取了三峡水电站作为研究对象进行实例验证。实验结果表明:研究所提出的模型方法指导水电站运行相比随机动态规划和常规调度图方法全年发电量提升效果明显,在2018年来水条件下模拟调度结果发电量分别提高了2.73%和2.31%,显著提高了来水不确定性条件下水电站运行发电效益,为解决水电站随机来水条件下长中短期嵌套预报调度实际工程技术难题提供了一种可行的实践理论方法工具,具有十分重要的理论研究意义和工程应用价值。     

Bayesian Stochastic Dynamic Programming for Hydropower Generation Operation Based on Copula Functions

Bayesian stochastic dynamic programming (BSDP) has been widely used in hydropower generation operation, as natural inflow and forecast uncertainties can be easily determined by transition probabilities. In this study, we propose a theoretical estimation method (TEM) based on copula functions to calculate the transition probability under conditions of limited historical inflow samples. The explicit expression of the conditional probability is derived using copula functions and then used to calculate prior and likelihood probabilities, and the prior probability can be revised to the posterior probability once new forecast information is available by Bayesian formulation. The performance of BSDP models in seven forecast scenarios and two extreme conditions considering no or perfect forecast information is evaluated and compared. The case study in the Ertan hydropower station in China shows that (1) TEM can avoid the shortcomings of empirical estimation method (EMM) in calculating the transition probability, so that the prior and likelihood probability matrices can be distributed more uniformly with less zeros, and the problem that the posterior probability cannot be calculated can be avoided; (2) there is a positive correlation between operating benefit and forecast accuracy; and (3) the operating policy considering reliable forecast information can improve hydropower generation. However, an incorrect decision may be made in the case of low forecast accuracy.

     

基于多元门限回归模型的葛洲坝入库流量分析

葛洲坝入库流量预报是葛洲坝电站安全稳定运行和制定发电计划的关键前提．同时也是三峡一葛洲坝梯级电站优化调度的重要技术支撑。对三峡出库与葛洲坝入库之间关系和不平衡性及流量传播时间进行分析。利用多年积累的三峡出库流量资料,通过水量平衡方程和多元门限回归模型对三峡出库流量进行不平衡修正．使修正后的三峡出库与实际出库流量差值明显减小,有效提高了发电计划的制定效率。     

基于贝叶斯统计与MCMC思想的水库随机优化调度研究

针对马尔柯夫随机动态规划中的维数灾问题,提出一种改进马尔柯夫随机动态规划方法,基于贝叶斯统计原理,采用马尔柯夫链蒙特卡洛方法(Markov Chain Monte Carlo,MCMC)从数学角度出发,推求出一定预报级别下的实际来流概率密度函数,建立与预报级别相关的实际来流概率矩阵,在考虑预报误差发生的情况下进行不确定性优化调度,并且将该方法计算结果与有无预报时段相结合的马尔柯夫随机动态规划方法计算结果进行比较。结果表明,该方法所得到的结果比马尔柯夫随机动态规划结果更加贴近实际多年平均发电量,并且能够有效地减少计算量,缩短计算时间,从一定程度上解决了维数灾问题,本方法为不确定性优化调度提供重要理论参考。     

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.

     

结合水库调度的小型水电站二次水量分配

根据水库调度的结果,电站在旬内的发电用水量是一定的。文中利用动态规划法,再次在旬内分配水量,结合小型水电站厂内经济运行计算,使电站在这一旬内总的发电量最大。实例计算表明,合理的水量旬内二次分配可以提高电站效益,使机组更好地处于高效率区运行。     

粒子群算法在水电站日优化调度中的应用

针对传统的动态规划方法求解水库优化调度问题存在的“维数灾”问题,给出一种全局随机优化算法[1]——粒子群优化算法并应用于水库日优化调度问题中。相对于动态规划,该算法原理简单,易编程,占用计算机内存少,能以较快的速度收敛到全局最优解,从而为分时电价环境下的水电站日优化调度问题提供了一种有效的解决办法。     

精细化调度下最大入库流量及水位优化控制研究——以葛洲坝水电站为例

以梯级发电量最大为目标,对葛洲坝水电站在不弃水前提下最大入库流量及水位控制方案进行了计算分析,并推荐了优化的调度方案。通过与调度实例进行对比分析,表明所提方案较实际调度优化。     

改进的投影寻踪技术在实际预报中的应用

针对传统的投影寻踪技术中投影与寻踪两个核心问题进行改进,用实数编码的遗传算法代替高斯一牛顿进行投影方向优化、利用非线性参数Hermite多项式代替非参数方法估计岭函数。建立基于改进的投影寻踪预测技术水电站入库流量预报模型,并将模型用于杂谷脑流域水电站的入库流量预测,研究表明改进的投影寻踪技术能够以较快速度收敛于模型全局最优解,研究成果为杂谷脑梯级水电站中期调度奠定了基础,也为其他流域水电站中期入库流量预报提供了重要借鉴。     

SAPSO算法在梯级水电站日优化调度中的应用

针对传统的动态规划方法求解水库优化调度阋题存在的"维数灾"问题,提出一种全局随机优化算法[1]--SAPSO算法及其在水库日优化调度问题中的应用.相对于动态规划,该算法原理简单,易编程实现,占用计算机内存少,能以较快的速度收敛到全局最优解,从而为分时电价环境下的水电站日优化调度问题提供了一种有效的解决办法.     

An Efficient Optimization Method for Long-term Power Generation Scheduling of Hydropower Station: Improved Dynamic Programming with a Relaxation Strategy

Integrating the characteristics of hydropower reservoir operations into optimization methods is an effective approach. Based on the concavity and monotonicity of hydropower reservoir operation with dynamic programming (DP), improved DP (IDP) with monotonicity in optimal decision-making can quickly search for an approximate optimal solution. However, IDP may not converge to the optimal solution of the long-term power generation scheduling (LPGS) problem of hydropower station due to the analysis conclusion of approximate monotonicity. Therefore, the relaxation strategy for expanding the search space based on the monotonicity of optimal decisions is introduced into IDP, which is named DP with a relaxation strategy (DPRS). The experimental results of Xiluodu, Xiangjiaba, and Three Gorges Reservoir (TGR) show that 1) the time complexity of DPRS and IDP decreases from the quadratic growth of DP with an increasing number of discrete states to linear growth; 2) DPRS and DP can obtain the optimal solution of the long-term power generation scheduling (LPGS) problem of hydropower station under the given discrete precision, whereas IDP searches for only an approximate optimal solution. Combined with the discussion with other relevant literature, all these results indicate that the DPRS has the strongest competitiveness in solving the LPGS problem of hydropower station, both in convergence accuracy and in calculation speed.

     

漳卫南灌区农业水资源优化配置研究

考虑到不确定条件下漳卫南灌区农业水资源管理的复杂性,为了解决当灌区水资源用户供水目标不能满足需求时的水资源优化配置问题,结合LFP模型与TSP模型的优点,开发了一种分式两阶段随机规划模型(FTSP)。选择漳卫南灌区最大控制性工程岳城水库的两个大型供水灌区作为验证实例,模型应用结果表明,不同决策情景所对应的经济效益和缺水风险不同,最优决策实现了经济效益和缺水风险之间的平衡;不同径流水平下,各用户的正常灌溉面积会发生相应变化,高径流水平时所有用户均能得到正常灌溉。     

利用水文预报进行水电站水库汛期预报调度

充分利用水文信息是协调水库防洪与兴利之间矛盾的有效方法；在满足防洪安全的前提下，可以在未发生洪水时期抬高水库运行水位，在洪水入库以前将库水位降至共限制水位，从而提高径流式不电站发电运行效益和调度水平。沙溪口水电站利用水文预报进行水库汛期预报调度效益显著。     

广西电网水电站群在线预报调度预警系统研发

以红水河梯级和郁江流域梯级水电站为重点,同时兼顾全流域,开展了广西电网水电站群在线流量预报、短临调度及预警监视系统研发。该系统可为水电区间降雨及梯级发电临时调整提供及时预警和快速应对方案,可有效提高水电洪前预泄增发效益,改善枯水期水电经济运行状态。     

基于耗水率动态规划模型的水电站水库优化调度

目前水电站水库优化调度常侧重于提高算法的精度和计算的速度,往往忽视了优化调度模型本身的合理性和准确性。综合耗水率是衡量水电站经济运行情况的重要指标。基于耗水率动态规划模型的水电站水库优化调度方法,依据水电站长期运行的历史资料,采用水电站综合耗水率参数作为水电站水库优化计算的基础,使优化结果更符合水库经济运行的实际要求。     

流域有众多小水电站的锦江水库降雨径流预报

根据降雨径流相关原理,结合锦江水库流域地理环境、水文、气象、上游小型水电站众多特点,将该流域划分为8个单元区,并在各单元区建立一个虚拟水库,代替众多小水电站调节水量的水库降雨径流预报模型,应用于锦江水库水文预报系统。2008年至今共6年的入库流量短期预报实践证明,该模型预报精度高,在水库防洪发电、水库调度应用中效果优良。     

A neuro-fuzzy model for inflow forecasting of the Nile river at Aswan high dam

River flow forecasting is an essential procedure that is necessary for proper reservoir operation. Accurate forecasting results in good control of water availability, refined operation of reservoirs and improved hydropower generation. Therefore, it becomes crucial to develop forecasting models for river inflow. Several approaches have been proposed over the past few years based on stochastic modeling or artificial intelligence (AI) techniques. In this article, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed to forecast the inflow for the Nile River at Aswan High Dam (AHD) on monthly basis. A major advantage of the fuzzy system is its ability to deal with imprecision and vagueness in inflow database. The ANFIS model divides the input space into fuzzy sub-spaces and maps the output using a set of linear functions. A historical database of monthly inflows at AHD recorded over the past 130 years is used to train the ANFIS model and test its performance. The performance of the ANFIS model is compared to a recently developed artificial neural networks (ANN) model. The results show that the ANFIS model was capable of providing higher inflow forecasting accuracy specially at extreme inflow events compared with that of the ANN model. It is concluded that the ANFIS model can be quite beneficial in water management of Lake Nasser reservoir at AHD.     

Shuffled complex evolution coupled with stochastic ranking for reservoir scheduling problems

This paper introduces an optimization method(SCE-SR) that combines shuffled complex evolution(SCE) and stochastic ranking(SR) to solve constrained reservoir scheduling problems,ranking individuals with both objectives and constrains considered.A specialized strategy is used in the evolution process to ensure that the optimal results are feasible individuals.This method is suitable for handling multiple conflicting constraints,and is easy to implement,requiring little parameter tuning.The search properties of the method are ensured through the combination of deterministic and probabilistic approaches.The proposed SCE-SR was tested against hydropower scheduling problems of a single reservoir and a multi-reservoir system,and its performance is compared with that of two classical methods(the dynamic programming and genetic algorithm).The results show that the SCE-SR method is an effective and efficient method for optimizing hydropower generation and locating feasible regions quickly,with sufficient global convergence properties and robustness.The operation schedules obtained satisfy the basic scheduling requirements of reservoirs.     

水库汛限水位实时动态控制模型研究

现行的汛限水位方法一般未能考虑预报信息，因而严重制约了水库汛期兴利效益的发挥。通过对实时调度中的可接受风险的研究，在调度期内控制防洪风险在可接受水平内；讨论实时调度与传统汛限水位之间的关系．由调度末水位耦合汛限水位，由此建立了带有机遇约束的水库汛限水位实时动态控制模型。结合三峡水库围堰发电期的汛期调度，进行了实例研究，结果表明，在不同的预报来水以及预报精度情况下，水库汛限水位实时动态控制模型能在不降低防洪标准的前提下，显著提高水库的兴利效益。