首页|基于改进PSO-GWO算法的渠系优化配水模型研究

基于改进PSO-GWO算法的渠系优化配水模型研究

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为减少渠系输配水过程中的水量损失,针对闸门调控时间各异和频繁启闭的问题,以精河灌区茫乡团结支渠支斗两级渠系渗漏损失量最小为目标建立渠系配水模型,首次采用"组间轮灌,组内续灌"的配水方式,通过改进PSO-GWO算法求解,确定斗渠最优轮灌编组、配水流量和灌水时间等重要参数,得出渠系渗漏损失量和算法迭代次数,并与粒子群算法、灰狼算法的求解结果进行对比。改进模型使灌水时间缩短了 0。62 d,支斗两级渠系水利用系数提高了 0。168,改进PSO-GWO算法迭代次数为3 次、渠系渗漏总量为 16。69 万m3,优于传统算法的配水结果。实例应用情况表明,改进算法具有更强的寻优能力和收敛性,并且模型在满足高效配水的同时,减少了闸门启闭次数,实现了集中调控,配水模式便捷,应用价值较高。
Research on Optimal Water Distribution Model of Canal System Based on Improved PSO-GWO Algorithm
In order to reduce the water loss in the process of water distribution in the canal system and in response to the issues of different gate regulation times and frequent opening and closing,the paper established a water distribution model of Tuanjie Branch canal in Jinghe ir-rigation area with the aim of minimizing the leakage loss of the two-stage canal system.It adopted the water distribution method of"inter-group rotational irrigation and intra-group continuous irrigation"for the first time,and solved the objective function by improved PSO-GWO algorithm,so as to determine the optimal rotation irrigation group,water distribution flow,and irrigation time and other important parameters of the branch canal,and obtained the leakage loss of the canal system and the number of iterations of the algorithm,then compared the re-sults with those of the particle swarm algorithm and the gray wolf algorithm.The improved model had shortened the irrigation time 0.62 days,increased the water utilization coefficient of the two-level canal system by 0.168,improved the iteration times of the PSO-GWO algorithm by 3 times,and reduced the total amount of canal leakage by 166 900 cubic meters,which was better than the water distribution results of the tra-ditional algorithm.The results show that the improved algorithm has stronger optimization ability and convergence,and the model can meet the requirements of high efficiency water distribution,reduce the number of gates opening and closing,realize centralized regulation and con-venient water distribution mode,which has high application value.

water distribution in channel systemwater seepagerotation irrigation groupimproved PSO-GWO algorithmparticle swarm optimizationgrey wolf algorithm

姚成宝、岳春芳、张胜江、郑秋丽

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新疆农业大学,新疆 乌鲁木齐 830052

新疆水利水电科学研究院,新疆 乌鲁木齐 830049

渠系配水 渗漏损失 轮灌编组 改进PSO-GWO算法 粒子群算法 灰狼算法

2025

人民黄河
水利部黄河水利委员会

人民黄河

北大核心
影响因子:0.494
ISSN:1000-1379
年,卷(期):2025.47(1)