采用Prony与粒子群算法的电力暂态信号分析

Analysis of Power System Transient Signal Based on Improved Prony Algorithm and PSO Algorithm

为了提高对含有谐波/间谐波、衰减直流分量和噪声的电力故障暂态信号的分析精度,提出了基于改进Prony算法与粒子群优化算法相结合的电力故障暂态信号分析方法。该文先采用多小波方法对信号进行消噪处理,再利用差分算法滤除衰减直流分量并对高频信号进行放大,以提高Prony算法的分析精度;然后利用改进Prony算法估计出信号中含有的频率个数和相关参量的粗略估计值,以此为基础建立电力参数模型,以得到的相关参量的粗略估计值作为算法的初始种群值,并估计出各参量的范围,最后采用粒子群优化算法对模型进行求解。仿真结果表明,所提方法能对所研究的电力故障暂态信号进行精确分析。

The method of analysis power system transient signal based on improved Prony algorithm and PSO algorithm is proposed to boost the analysis precision of the transient signal including harmonic,inter-harmonic and decaying DC component. The model of the prony algorithm has the excellent characteristic of exact describing transient signal and directly acquiring the frequency of signal. Denoising algorithm of multiwavelet and the differential algorithm is utilized jointly to eliminate decaying DC component and magnify the high frequency components to improve the analysis precision. The parameters of the signal are assumably estimated based on Prony algorithm to confirm the parameter model and the initial value of the PSO algorithm. The Matlab simulation results demonstrate that the algorithm achieves high accuracy and rapid convergence.