考虑径流预报及其不确定性的水电站水库调度研究
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摘要
目前,水利科学工作者已尝试应用各种中长期径流预报方法和优化算法来解决水电站水库(群)的预报、优化调度问题,并取得了令人瞩目的研究成果。然而,由于径流及其预报的不确定性,使得一些优化调度新方法仍存在理论与应用上的问题,需要在实际的应用中进一步深入研究。为此,本文围绕如何利用中期数值降雨预报改善水电站水库中长期径流描述模型和水库(群)优化调度模型而展开,着重解决雅砻江流域水电站水库径流预报调度等问题,但对其他流域预报调度研究具有一定的借鉴作用:结合水电站运行特性,首先分析了中期数值降雨预报在中长期径流预报及水电站水库调度中的可利用性,然后深入研究了考虑径流预报及其不确定性的径流描述和优化调度模型及其应用,最后对水库群预报调度系统重构和组件化进行了研究。主要研究成果如下:
(1)结合水电站运行特性,提出了一种基于决策树技术的中长期径流分级方法。该方法利用决策树技术分析二滩水电站多年的丰水期水文数据和发电调度资料,得出径流与调度决策出力之间的关系,称为径流分级决策树法。该分级方法能与实际的水电站防洪发电调度相结合,在一定程度上能反映出电站运行特性,使决策更加切合实际;与传统的径流分级方法相比,可减少弃水量,提高丰水期平均发电量。
(2)结合水电站运行特性,提出美国全球预报系统GFS中期数值降水预报信息可用性的分析方法。该方法不仅从降雨自身的特性出发,而且结合水电站特性利用决策树技术来划分降雨量级,并据此分析美国全球预报系统(GFS)中期数值降雨预报可利用性,包括基于决策树技术的降雨分级方法,GFS降雨分级预报精度分析,以及GFS降雨预报信息在旬径流预报和发电调度中的应用。研究表明,该方法在一定程度上反映了水电站运行特性,而且考虑GFS降水预报信息改进了发电调度决策,可明显提高发电效益,对GFS降雨预报信息在其他流域水库中的应用具有一定借鉴作用。
(3)提出了一种综合考虑径流预报及其不确定性的径流描述模型。该模型采用后验的径流状态转移概率和径流预报的可预测性概率来描述径流及其预报的不确定性。依据雅砻江流域枯、丰水期径流预报的不同特征,考虑不同预见期的流域径流预报信息,建立了符合二滩及锦屏一级～二滩梯级水电站运行特性的径流描述模型,并给出各自径流模型的水文状态变量的选择与离散,诸如先验的、后验的径流状态转移概率等条件概率的推求方法和流域总径流的分解方法等,它们对研究水电站调度模型是十分重要的。
(4)建立了考虑径流预报及其不确定性的水电站水库随机动态规划调度模型。考虑径流预报及其不确定性的径流描述模型能否指导发电调度,关键在于它能否改进调度决策达到提高发电效益的目的。为此,本文以二滩水电站和锦屏一级～二滩梯级水电站为例,建立了考虑径流预报及其不确定性的水电站水库随机优化调度模型,以探讨该模型对发电优化调度的改进潜力。研究表明,考虑径流预报及其不确定性有效地改善了已有的径流描述和发电优化调度模型,能明显提高水电站发电效益。
(5)引入重构和组件技术改善水库预报调度系统以适应用户功能需求变化。在水库预报调度系统的开发与应用实践中,用户会不断提出新的功能需求,因此有必要对系统进行重构和组件化研究以增强系统的复用性和扩展性。以基于图论的水库群预报调度系统为例,引入重构技术改善核心业务层,给出水库预报调度系统开发组件库Resrails,并基于Resrails实现了雅砻江流域梯级电站中长期预报调度系统。实际应用表明:基于重构和组件开发水库调度系统,可极大提高系统的复用性、扩展性和开发简易性,有利于开发人员集中精力研究水库群的预报调度模型等理论与应用。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
Researchers have utilized different algorithms to solve reservoir system optimization problems, and a large amount of research achievements have been made. However, there are still lots of problems to considered and explored in the population of their applications due to the uncertainties of inflow and its forecasts. This dissertation focuses on the use of Quantitative Precipitation Forecasts (QPFs) in medium-and-long-range runoff forecasting and hydropower operation of reservoirs system in Yalong river basin. Hydropower operation optimization is studied in depth using stochastic dynamic programming considering the uncertainty of inflow and forecasts. Then the primary achievements of this dissertation include as follows:
(1) A new method for classification of long-range runoff is proposed by decision tree technology. The method is established taking into account the characteristic of flood control and hydropower operation, which is different from the traditional ones, such as the cumulative occurrence frequency method. The results show that the proposed method performs relative well and higher hydropower production are also obtained.
(2) A simple rainfall-runoff hydrological model using the 10-day accumulated QPFs from Global Forecast System (GFS-QPFs) Forecasts is presented. Taking the Ertan reservoir as an example, 10-day accumulated GFS-QPFs over Yalong river basin are verified by using a three-category contingency table firstly. Then this paper presents the results from a proposed hydrological model. Results show that inflow forecast errors can be reduced considerably, compared with those from the currently used ARMA model by both quantitative and qualitative analysis. Finally, simulations of medium-range hydropower operation are also presented and simulations demonstrate that, the use of GFS-QPFs has improved in reservoir inflow predictions and hydropower operation of the Ertan hydropower station in the Yalong river basin during the wet season.
(3) A new inflow description model is proposed by addressing the uncertainty of inflow and its forecast. The randomness of the inflow is addressed through a posterior transition probability, and the uncertainty in flow forecasts is addressed through both the posterior flow transition probability and the predictive probability of forecasts. Taking the hydropower stations of Yalong river basin as examples, this study details the proposed model including the selection and Discretisation of hydrologic state variables, calculation of conditional probabilities,e.g. the prior and posterior transition probabilities, and the predictive probability of forecast, which will be the important inputs into the optimization operation models.
(4) A stochastic optimization operation model is presented to incorporate inflow forecasts with various lead-times as hydrologic state variables. Taking Ertan and Jinping I-Ertan cascade reservoirs for examples, this study details the models including the objective function, the development recursive equations, the steady state polices and theirs simulations. The results demonstrate that including inflow forecasts with various lead-times is beneficial to the Ertan hydropower generation, and the chosen operating policy can not only yield higher hydropower production, but also produce reasonable storage hydrographs effectively.
(5) Previous literatures focus on the overall structure and key technologies of reservoirs flood forecast and operation system (RFFOS), researches on system refactoring, however, are rarely done. Refactoring technique is introduced to improve the original RFFOS and a general RFFOS application framework is also given. Real application shows it is much easier for programmer to develop a RFFOS based on these extracted components, which will help the researcher of hydrological engineering to concentrate on the researches on models of flood forecasting and operation optimization policies.
Finally, a summary is given and some problems to be further studied are discussed.
(1)结合水电站运行特性,提出了一种基于决策树技术的中长期径流分级方法。该方法利用决策树技术分析二滩水电站多年的丰水期水文数据和发电调度资料,得出径流与调度决策出力之间的关系,称为径流分级决策树法。该分级方法能与实际的水电站防洪发电调度相结合,在一定程度上能反映出电站运行特性,使决策更加切合实际;与传统的径流分级方法相比,可减少弃水量,提高丰水期平均发电量。
(2)结合水电站运行特性,提出美国全球预报系统GFS中期数值降水预报信息可用性的分析方法。该方法不仅从降雨自身的特性出发,而且结合水电站特性利用决策树技术来划分降雨量级,并据此分析美国全球预报系统(GFS)中期数值降雨预报可利用性,包括基于决策树技术的降雨分级方法,GFS降雨分级预报精度分析,以及GFS降雨预报信息在旬径流预报和发电调度中的应用。研究表明,该方法在一定程度上反映了水电站运行特性,而且考虑GFS降水预报信息改进了发电调度决策,可明显提高发电效益,对GFS降雨预报信息在其他流域水库中的应用具有一定借鉴作用。
(3)提出了一种综合考虑径流预报及其不确定性的径流描述模型。该模型采用后验的径流状态转移概率和径流预报的可预测性概率来描述径流及其预报的不确定性。依据雅砻江流域枯、丰水期径流预报的不同特征,考虑不同预见期的流域径流预报信息,建立了符合二滩及锦屏一级～二滩梯级水电站运行特性的径流描述模型,并给出各自径流模型的水文状态变量的选择与离散,诸如先验的、后验的径流状态转移概率等条件概率的推求方法和流域总径流的分解方法等,它们对研究水电站调度模型是十分重要的。
(4)建立了考虑径流预报及其不确定性的水电站水库随机动态规划调度模型。考虑径流预报及其不确定性的径流描述模型能否指导发电调度,关键在于它能否改进调度决策达到提高发电效益的目的。为此,本文以二滩水电站和锦屏一级～二滩梯级水电站为例,建立了考虑径流预报及其不确定性的水电站水库随机优化调度模型,以探讨该模型对发电优化调度的改进潜力。研究表明,考虑径流预报及其不确定性有效地改善了已有的径流描述和发电优化调度模型,能明显提高水电站发电效益。
(5)引入重构和组件技术改善水库预报调度系统以适应用户功能需求变化。在水库预报调度系统的开发与应用实践中,用户会不断提出新的功能需求,因此有必要对系统进行重构和组件化研究以增强系统的复用性和扩展性。以基于图论的水库群预报调度系统为例,引入重构技术改善核心业务层,给出水库预报调度系统开发组件库Resrails,并基于Resrails实现了雅砻江流域梯级电站中长期预报调度系统。实际应用表明:基于重构和组件开发水库调度系统,可极大提高系统的复用性、扩展性和开发简易性,有利于开发人员集中精力研究水库群的预报调度模型等理论与应用。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
Researchers have utilized different algorithms to solve reservoir system optimization problems, and a large amount of research achievements have been made. However, there are still lots of problems to considered and explored in the population of their applications due to the uncertainties of inflow and its forecasts. This dissertation focuses on the use of Quantitative Precipitation Forecasts (QPFs) in medium-and-long-range runoff forecasting and hydropower operation of reservoirs system in Yalong river basin. Hydropower operation optimization is studied in depth using stochastic dynamic programming considering the uncertainty of inflow and forecasts. Then the primary achievements of this dissertation include as follows:
(1) A new method for classification of long-range runoff is proposed by decision tree technology. The method is established taking into account the characteristic of flood control and hydropower operation, which is different from the traditional ones, such as the cumulative occurrence frequency method. The results show that the proposed method performs relative well and higher hydropower production are also obtained.
(2) A simple rainfall-runoff hydrological model using the 10-day accumulated QPFs from Global Forecast System (GFS-QPFs) Forecasts is presented. Taking the Ertan reservoir as an example, 10-day accumulated GFS-QPFs over Yalong river basin are verified by using a three-category contingency table firstly. Then this paper presents the results from a proposed hydrological model. Results show that inflow forecast errors can be reduced considerably, compared with those from the currently used ARMA model by both quantitative and qualitative analysis. Finally, simulations of medium-range hydropower operation are also presented and simulations demonstrate that, the use of GFS-QPFs has improved in reservoir inflow predictions and hydropower operation of the Ertan hydropower station in the Yalong river basin during the wet season.
(3) A new inflow description model is proposed by addressing the uncertainty of inflow and its forecast. The randomness of the inflow is addressed through a posterior transition probability, and the uncertainty in flow forecasts is addressed through both the posterior flow transition probability and the predictive probability of forecasts. Taking the hydropower stations of Yalong river basin as examples, this study details the proposed model including the selection and Discretisation of hydrologic state variables, calculation of conditional probabilities,e.g. the prior and posterior transition probabilities, and the predictive probability of forecast, which will be the important inputs into the optimization operation models.
(4) A stochastic optimization operation model is presented to incorporate inflow forecasts with various lead-times as hydrologic state variables. Taking Ertan and Jinping I-Ertan cascade reservoirs for examples, this study details the models including the objective function, the development recursive equations, the steady state polices and theirs simulations. The results demonstrate that including inflow forecasts with various lead-times is beneficial to the Ertan hydropower generation, and the chosen operating policy can not only yield higher hydropower production, but also produce reasonable storage hydrographs effectively.
(5) Previous literatures focus on the overall structure and key technologies of reservoirs flood forecast and operation system (RFFOS), researches on system refactoring, however, are rarely done. Refactoring technique is introduced to improve the original RFFOS and a general RFFOS application framework is also given. Real application shows it is much easier for programmer to develop a RFFOS based on these extracted components, which will help the researcher of hydrological engineering to concentrate on the researches on models of flood forecasting and operation optimization policies.
Finally, a summary is given and some problems to be further studied are discussed.
引文
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