基于改进多目标粒子群算法的平原坡水区水资源优化调度  

Optimal operation of water resources in plain slope water area based on improved multi-objective particle swarm optimization algorithm

作　　者：王文君 方国华[1] 李媛[2] 闻昕[1] 郭玉雪[1] WANG Wenjun;FANG Guohua;LI Yuan;WEN Xin;GUO Yuxue(College of Water Conservancy and Hydropower Engineering,Hohai University,Nanjing 210098,China;Hydraulic Research Department,Nanjing Hydraulic Research Institute,Nanjing 210029,China)

机构地区：[1]河海大学水利水电学院,江苏南京210098 [2]南京水利科学研究院水工水力学研究所,江苏南京210029

出　　处：《水资源保护》2022年第2期91-96,127,共7页Water Resources Protection

基　　金：江苏省水利科技项目(2015084,2018033)。

摘　　要：在分析平原坡水区水资源优化调度特点的基础上,构建了协调泵站提水量和受水区缺水量两个目标的优化调度模型。针对传统粒子群算法存在的容易陷入局部极值点、早熟等缺点,从惯性因子及学习因子选择、外部档案维护和全局最优选取策略3个方面进行改进,对比改进多目标粒子群算法与传统NSGA-Ⅱ算法在求解测试函数中的表现,验证改进算法的可行性和优越性。对宿迁市黄河故道及以南地区水资源优化调度进行实例研究,采用改进算法求解模型得到Pareto前沿,结果显示,两个目标函数值分布范围较广,且各频率来水调度方案集在空间中分布均匀。The characteristics of the optimal operation of water resources in plain slope water area were analyzed,and an optimal operation model with two objectives involving the minimization of both water shortage and the amount of water pumping was established.The solutions obtained with the traditional multi-objective particle swarm algorithm frequently fall into local minima and are usually premature.The traditional algorithm was modified from the following three aspects:selection of inertial factors and learning factors,maintenance of external files,and selection of global optimum.Compared with the traditional NSGA-Ⅱ algorithm,the improved multi-objective particle swarm algorithm shows its validity and superiority in solving test functions.The old course of the Yellow River in Suqian City and the region to the south of it were used as a case to investigate the optimal operation of water resources,and the improved algorithm was used to find the Pareto front.The results show that the two objectives are widely distributed,and the Pareto solutions of incoming water at various frequencies are uniformly distributed in the space.

关 键 词：水资源优化调度 多目标优化 改进多目标粒子群算法 平原坡水区 黄河故道 

分 类 号：TV213.4[水利工程—水文学及水资源]