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南水北调东线江苏境内工程水资源优化配置方法研究
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摘要
南水北调是我国为了进一步实现水资源优化配置而开展的一项国家战略工程,工程建成后将有利于解决我国北方地区的水资源严重短缺问题,从而为我国的经济社会可持续发展提供基础保障。南水北调东线工程地处长江、淮河、黄河、海河流域下游,涉及津、冀、鲁、皖、苏五省市,是一个多水源、多用户、多阶段的的大型跨流域调水工程,工程已于2002年开工建设,2013年一期工程完成后,将经江苏省向北方调水。因此,如何对此复杂的供水系统进行科学合理的调度将是一个非常有意义且有必要的研究课题。
     当前,水资源系统优化问题受到了广泛关注,国内外学者对供水系统水资源优化配置理论及应用进行了大量的研究且取得了丰富的经验和成果。20世纪60年代以来,处理水资源系统问题多以简单的运筹学方法为主,然而随着所研究问题的逐步深化,传统优化理论和方法在处理非线性、高维、多目标、多约束等复杂问题方面日显掣肘。近年来,随着现代应用数学和计算机技术的不断发展以及水资源供需矛盾的日益突出,国内外学者针对复杂系统优化问题提出了诸如遗传算法、模拟退火算法、蚁群算法等人工智能计算方法,这些方法借助现代计算机作为工具,为水资源优化配置的研究发挥了巨大作用。本文在国内外相关研究的基础上,从理论和实践上系统分析了南水北调东线江苏境内工程水资源的优化配置问题,主要研究内容包括以下几个方面:
     (1)南水北调东线江苏境内工程是一个包括3个调蓄水库、9级提水泵站、若干条引水河道及5大类用水户(农业、工业、生活、生态环境及船闸用水户等)的“河-湖-梯级泵站”长藤结瓜供水系统。在用水户分类概化的基础上,本文结合蓄水工程的规模及控制水位、引水工程的布置情况及设计输水能力、提水工程的泵站规模及装机利用小时等因素,对各水文年的沿线用水户需水量等进行分析计算。
     (2)在水资源常规配置的基础上,本文提出了具有多决策变量的“河-湖-梯级泵站”单库供水系统水资源优化配置动态规划数学模型,模型以各区间缺水量(弃水量)的平方和最小为目标函数,各阶段的湖泊蓄水量为状态变量,各阶段抽水入湖量、湖泊放水量为决策变量。以南水北调东线一期工程“长江-洪泽湖”段调水工程为例,针对所研究问题的状态变量离散点少、决策变量可行域大且离散点多等特点,本文采用了基于动态规划与模拟退火相结合的混合算法(DP-SA)对该模型进行计算,结果表明:采用该模型进行优化调度,不但可以提高供水保证程度,而且可以减少系统的总抽水量,降低供水系统运行成本;同时,通过与动态规划逐次逼近法(DPSA)进行比较,可以得出混合算法在求解此类问题方面具有计算结果好、收敛速度快等优点。
     (3)为更好地解决大型跨流域调水工程水资源配置问题,本文在单库供水系统水资源优化配置研究的基础上,将模拟技术与离散微分动态规划方法(DDDP)相结合,提出了针对南水北调东线江苏境内工程的“河-湖-梯级泵站”多库供水系统水资源优化配置模型。该模型以整个供水系统的缺水量及抽水量最小作为综合目标:首先根据一定的湖泊运行规则按逆水流方向依次对各湖泊区间来用水进行模拟计算,以确定各湖泊区间在各时段的最大可供水量及可外调水量;在此基础上,以整个供水系统总抽水量最小为目标函数,各湖泊在每个时段的抽(弃)水量作为决策变量,建立了多库联合调度动态规划数学模型,并采用DDDP法对其进行求解。通过采用该模型对南水北调东线江苏境内工程进行水资源优化配置,结果表明,该模型提高了整个系统的供水保证率,同时实现了可供水量在各区间各时段的均衡分配;在50%、75%和95%频率时,江苏可实现最大外调出省水量达14.08亿m3、14.18亿m3和12.70亿m3;同时,供水系统总抽水量分别可减少51.34亿m3、94.87亿m3和28.19亿m3,可见通过优化调度,降低了系统运行成本,实现了本地水和外调水的联合优化配置。
The South-to-North water diversion project is a national strategic engineering to further realize the water resources optimal allocation in our country. When the project is completed, it will be a great action for solving the serious water shortage problem in northern China, so as to provide a basis guarantee for sustainable development of China's economic and social protection. The east route project is located in the lower reaches of Yangtze River, Huaihe River, Yellow River and Haihe River basin, involving five provinces and cities of Tianjin, Hebei, Shandong, Anhui and Jiangsu, Therefore it is a large-scale inter-basin water diversion project includes multiple water sources, multiple users and multiple stages. The first phase project has started its construction in2002and will transfer the water from Jiangsu to the north of China after the project is completed in2013. In view of this, how to carry out a scientific and rational scheduling for the complex water supply system will be a very meaningful and necessary research topic.
     At present, the water resources system optimization problem has attracted widespread attention, scholars at home and abroad do a lot of research on the theory and application of optimal allocation of water resources of the water supply system and get a lot of experience and results. Since the1960s, the simple methods of operations research was the major method to solve the water resources system problems. However, with the gradual deepening of the research questions, the traditional optimization theories and methods in dealing with non-linear, high-dimensional, multi-target, multi-constraint issues become increasingly constrained. In recent years, With the continuous development of modern applied mathematics and computer technology as well as the increasingly prominent contradiction between water supply and demand, the calculation methods of artificial computational intelligence such as genetic algorithms, simulated annealing, ant colony optimization algorithm have been proposed to deal with the complex system optimization problems. These methods have played a huge role for the optimal allocation of water resources by using the modern computer as a tool. On the basis of domestic and foreign related research, this paper analyzes systematically the optimal allocation of water resources for Jiangsu section of South-to-North Water Diversion East Route Project from the two aspects of theory and practice. The main research content and conclusions include the following aspects:
     (1) Combined with the basic situation of the first phase of South-to-North Water Diversion East Route Project in Jiangsu Section, this paper generalizes the complex water supply project into a rivers-lakes-pumping stations system, which is composed of three regulating reservoirs, nine-stage lift pumping stations, several diversion channels and five kinds of water users (including agriculture, industry, life, eco-environment and lock). On this basis, this paper analyzes the actual situation in various engineering, such as the scale and controlled water level of the water storage projects, the layout and water conveyance capacity of the water diversion projects, the scale and working hours of the lifting Projects and so on. At the same time, this paper classifies and generalizes the water users in each intake area, analyzes and calculates the runoff situation and water demand in each hydrological year.
     (2) A dynamic programming model with multiple decision variables for optimal water resources allocation of river-lake-pumping stations system is proposed, in which minimum sum of squares of water shortage (discarded water) in each section is set as the objective function, the water storage of the lake of each stage is defined as the state variable, the water volume to be pumped into the lake and the water release from the lake are expressed as decision variables. The Yangtze River-Hongze Lake section of South-to-North Water Diversion Project is taken as a case study. According to the characteristics that the discrete values of the state variable are relatively less while the feasible solution space of each decision variable is large and its more discrete values, this paper applies a hybrid method (DP-SA) using dynamic programming and simulated annealing combined by the authors to calculate the model. The application results show that using the proposed model to make optimal operation not only can improve the water-supply guaranteed rate, but also can decrease the water volume to be pumped which can reduce the operation cost of the water supply system. In comparison to dynamic programming with successive approximations(DPSA), we can obtain that the proposed hybrid method has better calculation results and faster convergence rate in solving this kind of problem.
     (3) In order to better solve the problem of water resources allocation in inter-basin water diversion project, this paper puts forward an optimal water resources allocation model for rivers-lakes-pumping stations system by combining simulation technology and discrete differential dynamic programming(DDDP) on the basis of the conventional water resources allocation. The model takes the minimum water shortage and pumping water volume as comprehensive objective function:At first, according to certain operation rules of lake, the inflow and water use in different hydrological year were simulated and calculated in order to determine the maximum available water supply volume and transferred water volume of each section. Based on this, a dynamic programming model for joint operation of multiple lakes is proposed, in which the minimum pumping water volume of the whole system is set as the objective function, the water volume to be pumped into the lake or discarded water from the lake is expressed as decision variable, and is solved by means of DDDP. The JiangSu section of South-to-North Water Diversion Project is taken as a study case, the results show that not only the water supply guaranteed rate of the whole system can be improved but also the equilibrium allocation of water supply volume among each section and each period can be realized. Secondly, by using the above mentioned model, we can obtain the maximum transferred water volume1408,1418and1270million m3out of JiangSu province in50%,75%and95%hydrological year. Thirdly, we can decrease the total pumping water volume5134,9487and2819million m3in50%,75%and95%hydrological year which can reduce the cost of the water supply system through optimal operation, and finally realize optimal joint allocation of local and transferred water resources.
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