排灌机械工程学报
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排灌机械工程学报  2011, Vol. 29 Issue (2): 127-132    DOI: 10.3969/j.issn.1674—8530.2011.02.008
泵站工程与给排水 最新目录 | 下期目录 | 过刊浏览 | 高级检索 Previous Articles  |  Next Articles  
大型泵站运行优化方法及其应用
冯晓莉, 仇宝云, 杨兴丽, 申 剑, 裴 蓓
(扬州大学能源与动力工程学院, 江苏 扬州 225127)
 Optimal methods and its application of large pumping station operation
Feng Xiaoli, Qiu Baoyun, Yang Xingli, Shen Jian, Pei Bei
(School of Energy and Power Engineering, Yangzhou University, Yangzhou, Jiangsu 225127, China)
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摘要 为了掌握适于求解具有多变量的大型泵站运行优化问题的现代优化方法,阐述了遗传算法(GA)、基本粒子群算法(PSO)与模拟退火粒子群算法(SA-PSO)的基本原理,分析了算法的异同点,从理论上得出PSO算法较GA算法更简单、更高效.以南水北调东线工程江都泵站系统为例,当泵装置扬程一定时,以各座泵站开机台数和水泵叶片角度为变量,运行费用最少为目标函数,并且满足总抽水流量、单机允许抽水流量以及开机台数等约束条件,建立运行方案优化数学模型,确定各座泵站开机台数、机组运行工况和日运行费用.分别采用遗传算法、基本粒子群算法和模拟退火粒子群算法求解,可行性规则处理约束条件,应用Matlab语言编制优化计算程序.结果表明:SA-PSO算法求解的泵站变角优化运行方案,较在设计角度运行的方案节省运行费用0.99%~4.22%,较GA,PSO算法最优解方案分别节省运行费用0.22%~2.80%和0.02%~0.40%;3种算法的运算时间分别为30,52,25 s.因此,SA-PSO算法较为适合于大型泵站运行优化问题的求解.
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关键词大型泵站   运行方案   优化方法   遗传算法   基本粒子群算法   模拟退火粒子群算法     
Abstract: In order to master modern optimal methods, which are suitable for solving large pumping stationoptimal operation with multivariables. Basic principles of genetic algorithms(GA), particle swarm optimization(PSO) and simulated annealing particle swarm optimization(SA-PSO) were introduced, and the similarities and differences were analyzed. It is concluded that PSO is more simple and efficient than GA. Taking Jiangdu pumping station system in Eastern Route of South to North Water Transfer Projectas an example, under the circumstances of certain pump assembly head, selecting the number of running pump units and blade setting angles of water pumps as variables, optimal mathematical models for pumping station operation schemes were established aiming at the least operation cost, meeting the constraint conditions such as total pumping discharge, allowed discharge of single pump and the number of running pump units. GA, PSO and SA-PSO were applied to solve the models respectively to determinethe number of running pump units, operation duties of pump units and daily operation cost of each pumping station. Constraint conditions were used to deal with feasible rules, and calculating procedurewas programmed with Matlab. The results indicate that the operation costs of the optimum schemes by adjusting pump blade setting angles with SA-PSO are 0.99%-4.22% less than that of the conventional schemes under design blade angles, and among the three optimum schemes, the operation cost of the optimum scheme based on SA-PSO is about 0.22%-2.80%, 0.02%-0.40% less than that based on GA and PSO respectively. Computing times of the three optimizing algorithms are 30, 52 and 25 s respectively. Therefore, SA-PSO is more suitable for solving large pumping station operation optimization problems.
Key wordslarge pumping stations   operation schemes   optimization methods   genetic algorithms   particle swarm optimization   simulated annealing particle swarm optimization   
收稿日期: 2010-08-07; 出版日期: 2011-03-30
基金资助:

全国百篇优秀博士学位论文作者专项基金资助项目( 2007B41) ; 江苏省水利科技重点项目( 2008048)

通讯作者: 仇宝云( 1962 ),男,江苏扬州人,教授,博士生导师( 通信作者,yzdxqby@ sohu.com) , 主要从事水泵与泵站工程研究.   
作者简介: 仇宝云( 1962 ),男,江苏扬州人,教授,博士生导师( 通信作者,yzdxqby@ sohu.com) , 主要从事水泵与泵站工程研究.
引用本文:   
. 大型泵站运行优化方法及其应用[J]. 排灌机械工程学报, 2011, 29(2): 127-132.
.  Optimal methods and its application of large pumping station operation[J]. Journal of Drainage and Irrigation Machinery Engin, 2011, 29(2): 127-132.
 
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