基于多特征融合的光伏系统串联直流电弧故障识别方法

A Multi-feature Fusion-Based Method to Recognize Series DC Arc Fault in Photovoltaic System

针对目前光伏系统中存在的串联直流电弧故障特征量少、识别定位困难等问题,提出一种基于多特征融合的光伏系统串联直流电弧故障识别方法。首先搭建实验平台,采集正常和串联直流电弧故障下的电流信号并利用小波变换进行降噪;其次,对降噪后信号提取时域上的电流均值变化率和电流周期最值差特征量,并提取频域上的各频带能量及能量比,利用集合经验模态分解(ensemble empirical mode decomposition,EEMD)得到各阶信号本征模态函数(intrinsic mode function,IMF),计算各阶IMF故障信号与正常信号余弦相似度,并提取相似度较低电弧的IMF能量熵特征;然后,以时域、频域、能量熵特征构成多维特征向量,构建故障电弧特征空间,通过实验确定故障空间边界参数,得到特征判据,根据多维特征判据实现直流电弧故障检测;最后,通过实验分析验证所提方法的准确性。

In allusion to such defects in current photovoltaic(abbr.PV)generation systems as less fault characteristic quantity of series DC arc and the difficulty to identify and locate them,a multi-feature fusion-based method to identify the series DC arc fault in PV generation system was proposed.Firstly,an experimental platform was built to collect current signals under normal operation of PV system and series DC arc fault occurred in PV system and the noise reduction was performed by wavelet transform.Secondly,for the post-noise reduction signals the change rates of the average of current and the characteristic quantity of cycle maximal difference in time-domain were extracted,and the energy and energy ratio of each frequency band in frequency domain were extracted,and by use of ensemble empirical mode decomposition(abbr.EEMD)the intrinsic mode function(abbr.IMF)of each order signal was obtained to calculate the cosine similarity between each order IMF fault signal and normal signal,and the energy entropy feature of IMF of the arc with lower similarity was extracted.Thirdly,the feature space of fault arc was built by the multi-dimensional feature vector that was constituted by the features in time domain,frequency domain and the feature of energy entropy,and the boundary parameters of fault space were determined by experiments,and then the characteristic criteria in time-domain,frequency-domain and that in energy entropy were obtained,and according to multi-dimensional characteristic criteria the DC arc fault detection could be implemented.Finally,both feasibility and accuracy of the proposed method are verified by the analysis on the results of experiments.