基于Pareto最优解的梯级泵站双目标优化调度  

The double objectives optimal scheduling of multistage pumping stations based on Pareto-optimal method

作　　者：梁兴[1,2] 刘梅清[1] 燕浩[1] 吴远为[1] 林鹏[1] 

机构地区：[1]武汉大学动力与机械学院,湖北武汉430072 [2]南昌工程学院机械与电气工程学院,江西南昌330099

出　　处：《武汉大学学报（工学版）》2015年第2期156-159,165,共5页Engineering Journal of Wuhan University

基　　金：国家自然科学基金项目(编号:50879062);湖北省水利重点科研课题(编号:HBSLKJ201307)

摘　　要：针对大型梯级泵站运行特点,用调度周期内的机组启动次数衡量维修成本,建立以抽水电费最小和机组启动次数最少为优化目标,以调度周期内流量分配为决策变量的双目标优化调度模型,并基于Pareto最优解理论,开展混合粒子群求解算法研究,并将双目标优化调度模型应用于工程实际.研究表明,双目标优化调度能够反映抽水电费与机组维修费用之间的内在联系,即抽水电费最优解随着机组启动次数的增加,呈现出先减少后增大的趋势,但在某一范围内,随着机组启动次数的增加,抽水电费最优解变化幅度较小,系统最优调度方案在此区间内选择不仅能够有效地降低抽水电费,也能够避免维修成本的急剧增加,这为梯级泵站调度决策提供了有力的理论依据.The mathematical model is established to optimize the scheduling of multistage pumping sta- tions, which use the minimum pumping costs and the minimum start-up times of units as the optimal objec- tives. And then the particles swarm optimization combined with the Pareto-optimal method is used to solve the optimal scheduling model. The research results show that this optimal model can reveal the internal re- lationship between pumping costs and maintenance costs easily; with the start-up times of units increase, the optimal pumping costs decrease first and then increase; but in a certain range, the change of optimal pumping costs is smaller with the start-up times of units increase; so the optimal scheduling is best to choose in this range; and this research is not only helpful to decrease the pumping costs, but also to avoid the maintenance costs increase.

关 键 词：双目标优化调度 梯级泵站 PARETO最优解 粒子群算法 

分 类 号：TV675[水利工程—水利水电工程]