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本文研究确定来水条件下库群优化调度问题,建立了数学模型并提出了状态(水位)极值逐次优化解法(SEPOA),证明了四个定理,这些定理表明,采用SEPOA方法从某一可行调度线开始,计算将收敛稳定于唯一的最优调度线.在水电站的优化调度及库群优化补偿计算中,几乎所有的数学规划方法,如线性规划、非线性规划以及各种动态规划方法都曾采用.这些研究克服了维数障碍,也带来新的问题,如目标函数极值的性质问题,局部极值与整体极值的关系问题,而这些对于实际问题是十分重要的.此外,各种方法的有效程度,极大的决定于实际问题的性质特点和具体条件,而过去这一点往往没有引起足够的重视.水库问题的优化算法,应更多的建立在问题本身所固有的特征和特性上.从这一点出发,我们着重于水库本身的特点,并力求在较为一般的条件下,研究一种算法,并讨论计算的收敛,最优解的存在及唯一性.
In this paper, we study the problem of reservoir group scheduling problem under runoff condition, establish a mathematical model and propose a state-of-the-water (SWP) extreme sequential optimization solution (SEPOA), proving four theorems. These theorems show that using SEPOA method from a feasible At the beginning of the scheduling line, the calculation will converge and stabilize to the only optimal scheduling line. In the optimal operation of hydropower station and reservoir group optimization, almost all mathematical programming methods, such as linear programming, nonlinear programming and various dynamic programming methods These studies have overcome dimensionality barriers as well as brought new problems such as the nature of the extremum of the objective function, the relationship between the local extremum and the overall extremum, and these are very important for practical problems.In addition, The effectiveness of each method depends greatly on the nature and specific conditions of the actual problem, which has often not been given sufficient attention in the past.Optimization algorithms for reservoir problems should be more based on the inherent characteristics of the problem itself And characteristics. From this point of view, we focus on the characteristics of the reservoir itself, and strive to study an algorithm under more general conditions, and discuss the calculation of income , There is an optimal solution and unique.