基于改进遗传算法的水库群防洪联合优化调度研究及其应用

Research and application of joint optimal operation for flood defense of reservoir group based on improved genetic algorithm

“预演”是流域防洪“四预”的重要环节,进行大型水库或水库群的调度计算,是“预演”的重要手段,对不同调度方案结果进行分析,是确定“预案”的前提和基础。水库群防洪联合优化调度是一项重要的可以提高水库防洪能力的非工程性防洪措施,起到调节洪峰、储蓄洪水、减轻甚至避免洪涝灾害的作用。以淮河干流王家坝以上流域的出山店、南湾及宿鸭湖3座大型水库为例,以2020年7月场次洪水作为输入,改变其以往独立的、按规则调度的方式,在保障下游防洪安全的前提下,以3座水库占用的最大防洪库容之和最小为目标进行水库群防洪联合优化调度,并建立相应模型通过改进遗传算法对其进行求解。结果表明,改进的遗传算法节省了模型用于确定惩罚系数的时间并使模型应用更为便捷,相较于规则调度,优化调度可以保证该流域水库及下游控制站点的安全,同时3座水库占用的库容总和可减少1.23亿m3。

Joint optimal operation for flood defense of reservoir group is an important non-option measures which can improve the flood control capacity of reservoir, and plays the role in regulating flood peak, storing floodwater, mitigating or even avoiding flood disasters. Taking the three large reservoirs(Chushandian, Nanwan and Suyahu) above Wangjiaba station in the main stream of Huaihe River as an example, taking the July 2020 flood as the input, changing its previous independent and regular regulation mode, the joint optimal regulation for flood control of reservoir groups was carried out with the aim of minimizing the maximum flood storage capacity occupied by three reservoirs under the premise of ensuring the safety of flood in the downstream. The corresponding model was established and solved by improved genetic algorithm. The results showed that, the improved genetic algorithm saved the time for the model to determine the penalty coefficients and made the model application more convenient. Compared with the regular regulation, optimal operation could ensure the safety of reservoirs and downstream control stations in the river basin, and the total flood storage capacity occupied by the three reservoirs could be reduced by 123 million m3.