直流电能表计量信号自适应降噪方法

直流配电网包含DC/DC变换器等电力电子器件,非线性特性显著,导致直流输出端电压、电流信号存在大量纹波,需通过滤波降噪处理提升直流电能计量的准确性。针对现有的滤波降噪方法参数设置缺乏优化、滤波降噪效果尚待提升问题,本文提出基于自适应变分模态分解与小波阈值去噪相结合的直流电能计量数据降噪方法。建立输出端直流电压、电流信号变分模态分解的参数最优化模型,并联合互信息分析,实现原始信号的有效模态分量与噪声模态分量的自适应区分。在此基础上,建立以信噪比、均方根误差、平滑度、相关系数复合评价指标最优的小波阈值去噪参数最优化模型,实现噪声模态分量的最优滤波降噪。通过实测数据计算分析,验证所提方法的有效性。

Research on adaptive noise reduction method for direct current energy measurement data

DC power distribution network contains DC/DC converters and other power electronic devices, which have significant nonlinear characteristics, resulting in a large number of ripple signals in DC output voltage and current signals. It is necessary to improve the accuracy of DC energy measurement by filtering and noise reduction. Aiming at the problem that the parameter setting of the existing filter denoising method is not optimized and the effect of filter denoising needs to be improved, this paper proposes a method of DC energy measurement data denoising based on adaptive variational mode decomposition and wavelet threshold denoising. The parameter optimization model of variational mode decomposition of DC voltage and current signal is established, and the mutual information analysis is combined to realize the adaptive differentiation between the effective mode component and the noise mode component of the original signal. On this basis, the optimization model of wavelet threshold denoising parameters is established with the composite evaluation indexes of signal-to-noise ratio, root-mean-square error, smoothness and correlation coefficient, and the optimal filtering of noise modal components is realized. The validity of the proposed method is verified by calculating and analyzing the measured data.