两阶段粒子群算法在水电站群优化调度中的应用

以水电站群最小出力约束下的发电量最大为目标建立了水电站群优化调度数学模型,采用两阶段粒子群算法求解。在按目标函数进行进化计算之前,先进行以最小平均出力最大为目标的第一阶段优化,并在粒子群中引入初始可行解,以提高粒子群的质量和求解效率。以云南电网统调的7库14站主力水电站群系统为例进行了计算,结果表明,该算法能有效克服“维数灾”问题,能得到高性能的优化调度结果。

Application of Two-Stage Particle Swarm Optimization Algorithm in Optimized Dispatching of Hydropower Station Group

The authors build a mathematical model for optimized dispatching of hydropower station group in which the maximum electric energy generation is taken as objective function as well as the least output of station group as the constraint,and this model is solved by two-stage particle swarm optimization(PSO)algorithm.Before the evolutionary calculation of the proposed objective function,the first stage optimization in which the maximization of least mean output is taken as objective is carried out at first and led the initial feasible solution into particle swarm to improve the quality of particle swarm and solving efficiency.This algorithm is applied to a hydropower station group including 7 reservoirs and 14 hydropower stations in Yunnan,calculation results show that the trouble caused by curse of dimensionality can be effectively overcome by the proposed algorithm and optimized dispatching results with high performance can be obtained.