电力系统保护与控制
電力繫統保護與控製
전력계통보호여공제
POWER SYSTM PROTECTION AND CONTROL
2013年
17期
18-24
,共7页
徐方维%刘亚梅%杨洪耕%肖先勇
徐方維%劉亞梅%楊洪耕%肖先勇
서방유%류아매%양홍경%초선용
电压暂降%改进S变换%分类%相似度
電壓暫降%改進S變換%分類%相似度
전압잠강%개진S변환%분류%상사도
voltage sags%generalized S-transform (GST)%classification%similarity
电压暂降分类识别是合理选择电能质量治理方案的前提。提出一种基于改进S变换的电压暂降识别方法。首先根据电压暂降特征频率范围自适应确定改进S变换的调节因子,计算所得模时频矩阵作为电压暂降标准模板;再比较待测试暂降的改进S变换模矩阵特定频段与各标准模板之间的相似度,实现扰动分类。在比较相似度值的过程中,为凸显不同暂降类型的相似性及差异性,采用分频逐行计算相似度值,从而实现异类模板差异最大化。该方法充分挖掘各类暂降的特征差异,通过简单的相似度计算对扰动进行分类,无需添加辅助分类器。仿真和大量实测数据研究表明,该方法分类过程简单,抗干扰能力强。
電壓暫降分類識彆是閤理選擇電能質量治理方案的前提。提齣一種基于改進S變換的電壓暫降識彆方法。首先根據電壓暫降特徵頻率範圍自適應確定改進S變換的調節因子,計算所得模時頻矩陣作為電壓暫降標準模闆;再比較待測試暫降的改進S變換模矩陣特定頻段與各標準模闆之間的相似度,實現擾動分類。在比較相似度值的過程中,為凸顯不同暫降類型的相似性及差異性,採用分頻逐行計算相似度值,從而實現異類模闆差異最大化。該方法充分挖掘各類暫降的特徵差異,通過簡單的相似度計算對擾動進行分類,無需添加輔助分類器。倣真和大量實測數據研究錶明,該方法分類過程簡單,抗榦擾能力彊。
전압잠강분류식별시합리선택전능질량치리방안적전제。제출일충기우개진S변환적전압잠강식별방법。수선근거전압잠강특정빈솔범위자괄응학정개진S변환적조절인자,계산소득모시빈구진작위전압잠강표준모판;재비교대측시잠강적개진S변환모구진특정빈단여각표준모판지간적상사도,실현우동분류。재비교상사도치적과정중,위철현불동잠강류형적상사성급차이성,채용분빈축행계산상사도치,종이실현이류모판차이최대화。해방법충분알굴각류잠강적특정차이,통과간단적상사도계산대우동진행분류,무수첨가보조분류기。방진화대량실측수거연구표명,해방법분류과정간단,항간우능력강。
Classification of voltage sags is the precondition for choosing the right power quality management measures. This paper proposes a new voltage sag identification method based on the module matrix of generalized S-transform. It firstly determines the regulatory factor of improving the S-transform by the main frequency constituents of sags and then calculates the modulus matrixes of the S-transform to form the standard templates. The sags are classified through the analysis of the similarity between the specific region of the matrix of the test sags and the standard templates. In the process of similarity calculation, for enlarging the similarities and differences among standard templates, the idea of calculating similarities at different frequencies is proposed, thus making the differences maximized. This method sufficiently excavates the characteristic differences among sags;no extra classification process is needed. Simulation and actual data analysis show that this method is easy to be implemented and has high accuracy and noise robustness. This work is supported by National Natural Science Foundation of China (No. 51077095).