变尺度混沌蜂群算法在梯级库群优化调度中的应用  

Application of Variation-scale Chaotic Bee Colony Algorithm in Optimal Schedule of Cascade Reservoirs

作　　者：张德发[1] 周建中[1] 卢鹏[1] 莫莉[1] 肖舸[2] 

机构地区：[1]华中科技大学水电与数字化工程学院,湖北武汉430074 [2]三峡水利枢纽梯级调度通信中心,湖北宜昌443133

出　　处：《水电能源科学》2014年第4期46-50,共5页Water Resources and Power

基　　金：国家自然科学基金重点项目(51239004);国家自然科学基金青年科学基金项目(51109086)

摘　　要：针对流域梯级水电站长期优化调度模型存在高维、非凸、非线性等特点,提出一种改进的变尺度混沌蜂群算法(VCBA),通过引入混沌方程和余弦收缩策略,使其具有更强的全局收敛能力和更快的收敛速度。以丰枯分时电价下金沙江下游梯级水电站群长期优化调度作为工程背景进行实例研究,并将计算结果与基本蜂群算法(BA)和粒子群算法(PSO)进行比较。结果表明,VCBA求解梯级水电站长期优化调度问题收敛速度快且优化结果精度较高,满足实际优化运行需求,具有很高的工程应用价值。Aiming at the characteristics of high dimension, non convex and nonlinearity in long term optimal scheduling model of cascade hydropower stations, the author proposed an improved variation scale chaotic bee colony algorithm （VCBA）. By introducing chaos equation and cosine contraction strategy, the VCBA has more stronger global convergence ability and faster convergence rate. Taking long term optimal schedule of cascade hydropower station groups in the lower reaches of Jinshajiang River considering time of use electricity price as an engineering background, the results are compared with the basic bee colony algorithm （BA） and PSO algorithm. It shows that VCBA has a fast convergence rate and the accuracy of optimal result is high, and the result can meet the demand of practical optimal operation, which has a very high engineering value in use.

关 键 词：梯级水电站 优化调度 蜂群算法 混沌方程 余弦收缩 

分 类 号：TV697.11[水利工程—水利水电工程]