大型泵站运行优化方法及其应用

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.

Optimal methods and its application of large pumping station operation

In order to master modern optimal methods,which are suitable for solving large pumping station optimal 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 Project as an example,unde...