基于proony算法和神经网络的电力系统暂态信号分析

Hua Ouyang, Jialin Wang
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引用次数: 6

摘要

提出了一种基于改进proony算法和神经网络的电力系统暂态信号分析方法,提高了含谐波和间谐波暂态信号的分析精度。proony算法模型具有准确描述暂态信号和直接获取信号频率的优良特性。利用proony算法对信号的频率分量进行假设估计,首先确定神经细胞的数量和神经网络的起始参数。接下来,将每个频率作为权重进行调整,以估计基波、谐波和间谐波的频率值和幅值。Matlab仿真结果表明,该算法精度高,收敛速度快。
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Power system transient signal analysis based on Prony algorithm and neural network
A method of power system transient signal analysis based on improved Prony algorithm and neural network is used here to improve the accuracy of analysis of the transient signal with harmonic and inter-harmonic. The model of the Prony algorithm has the excellent characteristic of exactly describing transient signal and directly acquiring the frequency of signal. The frequency components of the signal were estimated assumably using Prony algorithm to confirm the amount of nerve cells and the beginning parameter of neural network firstly. Next, each frequency was treated as weight to be adjusted to estimate frequency values and amplitudes of the base wave, harmonics and inter-harmonics. Matlab simulation results demonstrated that the algorithm achieved high accuracy and rapid convergence.
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