摘要
针对传统的Prony算法运算效率较为低下,抗噪性能较弱的问题,文章提出一种改进Prony算法的高电压电网故障检测方法。该方法将粒子群算法与Prony算法进行结合,首先基于Prony算法可以建立包含谐波分量幅度值、衰减因子和频率等一系列的参数的模型,然后利用粒子群优化算法对谐波幅值、相位和频率进行辨识,避免了传统Prony算法中由于噪声问题造成的信号频率难以提取的弊端。通过仿真证明了文章算法具有极强的可靠性和较高的运算效率。
In order to improve the problems of weak antinoise performance and computation efficiency of the traditional Prony algorithm,an improved Prony algorithm of high voltage power grid fault detection technology is put out.This method combines particle swarm optimization（PSO）algorithm and Prony algorithm.First of all,the model contain harmonic component amplitude value,attenuation factor and frequency and so on a series of parameters is established based on Prony algorithm,then the particle swarm optimization algorithm is used to identify the harmonic amplitude,phase and frequency.The algorithm avoids the problem.which the signal frequency is difficult to extract,caused by noise of the traditional Prony algorithm.By a series of numerical examples,the improved performance is show in this paper,the improved Prony with strong reliability and higher operation efficiency.
作者
李琳
Li Lin(Branch of information, Changzhou Institute of Engineering Technology, Changzhou 213164, China)
出处
《可再生能源》
CAS
北大核心
2018年第4期539-543,共5页
Renewable Energy Resources
基金
江苏省科技厅重点研发项目(BE2017067)
关键词
故障检测
PRONY算法
粒子群优化算法
fault detection
Prony improved algorithm
particle swarm algorithm
