【摘要】 为了准确辨识电能质量扰动的类型,以实现电能质量问题的有效治理,提出一种基于改进希尔伯特-黄变换(Hilbert-Huang transform,HHT)和决策树的电能质量扰动辨识方法。该方法先采用改进的基于斜率的方法(improved slope based method,ISBM)抑制希尔伯特-黄变换算法的端点效应,然后利用改进的HHT方法进行电能质量扰动信号的分析;从得到的瞬时频率曲线中提取频率成分、扰动持续时间和扰动持续期间频率3个特征量,并从瞬时幅值曲线中获取扰动期间电压幅值;最后构建分类决策树,将这4个特征量作为判断依据,实现扰动信号的分类和识别。根据各类电能质量扰动信号的数学模型,产生大量的测试样本进行仿真测试,结果证明了该方法的有效性和准确性,并且与现有的2种扰动辨识方法进行对比,结果表明该方法具有更高的识别准确率,能准确辨识出电能质量扰动的类型。更多还原

【Abstract】 In order to accurately identify the type of pow er quality disturbance for the effective governance of pow er quality problems,this paper proposes a new identification method for pow er quality disturbance based on the improved Hilbert-Huang transform( HHT) and decision tree. Firstly,pow er quality disturbance signals are analyzed through HHT algorithm w ith the improved slope-based method( ISBM) inhibiting the endpoint effect. Then,the frequency components,the disturbance duration and the frequency during the disturbance duration can be extracted from the obtained instantaneous frequency curve. And from the instantaneous amplitude curve,the voltage amplitude during the disturbance duration can be obtained. Finally,by using these 4 characteristics as the judgment of the constructed decision tree,the disturbance signal is successfully classified and recognized. According to the mathematical model of each kind of pow er quality disturbance signal,a large number of samples are produced to conduct the simulation tests. The simulation results prove the effectiveness and accuracy of the proposed method. And compared w ith the existing tw o identification methods,the results show that this method has higher identification accuracy,w hich can identify the type of pow er quality disturbance quite accurately.更多还原