基于自适应遗传算法的系统PSS参

多机电力系统中，电力系统稳定器PSS（Power System Stabilizer）的优化配置是一个复杂的非线性优化问题。一般PSS的配置包括其安装地点的选择和参数的优化。先根据参与因子法对PSS的安装地址进行选择，而后重点研究运用改进的自适应遗传算法(AGA, Adaptive Genetic Algorithm)对多机系统PSS参数进行优化。这种方法中交叉率和变异率能够随适应度自动改变，而不是恒定不变。该方法的优点是改善了传统的遗传算法(GA, Genetic Algorithm)中容易出现的“早熟”现象，提高了寻优过程的收敛性和稳定性。仿真结果表明，采用的自适应遗传算法在收敛性、计算时间和参数稳定上都优于传统遗传算法，将经过参数优化后的PSS加装到系统中，不仅可以克服低频振荡现象，而且使系统的暂态稳定性和静态稳定性都得到大幅度增强。

Parameter Optimization of Power System Stabilizers Using Adaptive Genetic Algorithms

In a multi-machine power system,it is a quite complicated problem to adjust the parameters of power system stabilizers.Normally,the problem includes selection of the site where the PSS should be installed and optimization of the PSS parameters.In this paper,the installation site of the PSS is determined by participating factors firstly,then an improved adaptive genetic algorithms(AGA) is used to optimize the PSS parameters.The crossover probability and the mutation probability in AGA are changed according to the fitness,and they are not constant just as in GA.Compared with GA,AGA can avoid premature phenomenon and improve solution quality.Simulation results show the effectiveness of the proposed optimization method,and prove that AGA is superior to GA in term of convergence,solution speed and parameter steadiness,and the power system with optimized PSS parameters possess good robustness in various system loading conditions.