基于改进遗传算法的发电机调速器侧模糊PSS优化设计

Optimization design of fuzzy PSS for governor of generator based on an improved GA

基于模糊控制理论设计了发电机组调速器侧模糊电力系统稳定器,采用遗传算法优化其参数以克服模糊控制器参数设计的主观性。为了提高多参数控制器参数优化的速度和精度,对传统单点交叉遗传算法进行改进,提出了一种首尾轮换交叉遗传算法。该方法交替采用尾部和头部单点交叉,保证了各参数参与优化的概率基本均等。采用该算法对某水轮发电机组调速器侧模糊电力系统稳定器的参数进行优化计算,表明其优化速度和精度较试探法和传统单点交叉遗传算法有显著提高。

A fuzzy governor power system stabilizer（FGPSS） is designed for a generator based on the fuzzy control theory and its parameters are optimized by using Genetic Algorithm （GA） to overcome the subjectivity in designing fuzzy controller＇s parameters. In order to raise the speed and accuracy, the conventional single-point crossover GA is improved and a new GA named Head-and-Tail Alternate Crossover GA is proposed. The head-crossover and tail-crossover is used alternately in the algorithm, which ensures that the optimized probability of every parameter is approximately equal. The parameters of FGPSS for a hydro-generator unit are optimized using the algorithm and the result indicates that the algorithm is more quickly and precisely than Error-and-Trial method and conventional GA.