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Operation Policies through Dynamic Programming and Genetic Algorithms, for a Reservoir with Irrigation and Water Supply Uses
Water Resources Management ( IF 3.9 ) Pub Date : 2021-03-12 , DOI: 10.1007/s11269-021-02802-w
Rosalva Mendoza Ramírez , Maritza Liliana Arganis Juárez , Ramón Domínguez Mora , Luis Daniel Padilla Morales , Óscar Arturo Fuentes Mariles , Alejandro Mendoza Reséndiz , Eliseo Carrizosa Elizondo , Rafael Bernardo Carmona Paredes

In this study, operation policies were obtained for a reservoir in Michoacán, Mexico, used for irrigation and domestic water supplies. The main purpose of these policies is to optimize the uses of the water, an increasingly scarce resource everywhere. Two optimization methodologies were used; stochastic dynamic programming, that provides release decisions for each stage, and genetic algorithms coupled with a reservoir operation simulation program, to achieve annual release curves. The operation of the reservoir was evaluated using historical inflow records. Monthly requirements for crop cycles, as well as the volumes of spills and deficits were examined. Both methodologies gave inverse relationships between deficits and spilled volumes. While both methodologies proved efficient in achieving the objectives, the results of the stochastic dynamic programming showed a better performance for this system.



中文翻译:

通过动态规划和遗传算法的水库,用于灌溉和供水的水库

在这项研究中,获得了墨西哥米却肯州一个水库的运营政策,该水库用于灌溉和生活用水。这些政策的主要目的是优化水的使用,水是世界上越来越稀缺的资源。使用了两种优化方法:随机动态规划(提供每个阶段的释放决策)以及遗传算法与储层运行模拟程序相结合,以实现年度释放曲线。使用历史流入记录对储层的运行进行了评估。检查了作物周期的每月需求以及溢出和亏缺的数量。两种方法都给出了赤字和溢出量之间的反比关系。尽管两种方法都证明可以有效地实现目标,

更新日期:2021-03-15
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