EEMD在电力谐波检测中的应用

摘要

为了克服基于经验模态分解方法EMD在谐波检测中出现的模态混叠问题,提出采用基于总体平均经验模态分解(EEMD)的希尔伯特-黄变换(HHT)谐波检测方法.采用EEMD对含有谐波的负载电流进行分解,获得固有模态函数后,再进行HHT,求出基波以及各次谐波的幅值、相位、瞬时频率等信息.该算法在负载突变时自适应能力强,检测精度高,实时性好.仿真实验结果表明,EEMD方法在分解过程中不会出现模态混叠现象,克服了EMD的不足,同时基于数据采集卡的谐波检测平台的测试结果进一步证明了该方法的可行性.%In order to overcome the mode mixing deficiency in the harmonic detection method based on empirical mode decomposition(EMD),a new harmonic detection method is proposed based on Hilbert-Huang transform(HHT)by us-ing ensemble empirical mode decomposition(EEMD). First,the load current containing harmonic is decomposed by EEMD,then the intrinsic mode function is obtained,and HHT is performed to find amplitude,phase,instantaneous frequency and other information of the fundamental wave and every harmonic. The EEMD method has strong adaptive ability,high accuracy and good real-time performance when the load mutates. The simulation results show that the EEMD method can avoid mode mixing in the decomposition process,which overcomes the disadvantage of EMD. At the same time,test result by harmonic detection platform based on data acquisition card further proves the feasibility of the proposed method .