基于GSFLA的电力系统谐波估计算法

针对非线性动态负载引起的谐波难于检测的问题，提出了一种新的谐波估计算法。该算法借助蛙跳算法（SFLA）的全局搜索性对未知参数进行优化估计；引入高斯分布估计算法（GEDA）的思想，对蛙群中适应度好的蛙进行分布估计再生，提高收敛速度；结合进化代数改进蛙跳规则以改善局部搜索性能。实验仿真数据显示，与PSO算法相比，振幅平均估计精度提高了5．3％，相角平均估计精度提高了4．7°。研究表明，该算法（GSFLA）用于电力系统的谐波估计有更快的收敛速度和估计精度。

Harmonic Estimation Algorithm Based on GSFLA for Power System

Aimed at the difficulty in estimation of harmonics caused by nonlinear dynamic loads, a new method of harmonics estimation is pro- posed. The global searching capability of the shuffled frog leaping algorithm （ SFLA ） was used to estimate the unknown parameters. The thoughts of Gaussian distribution estimation algorithm （GEDA） were introduced and some of frog population with best fitness was split based on GEDA to improve the convergence speed. Leapfrog rules were improved by evolution generations to optimize the local performance. Com- pared with PSO algorithm, experimental simulation data showed that average estimation accuracy of harmonics amplitude was enhanced by 5.3% ,and the average estimation accuracy of harmonics phase was enhanced by 4.7°. The research shows that the proposed glgorithm （ GS- FLA） has faster convergence speed and higher estimation precision in power system harmonics estimation.