电能质量扰动小波变换检测与识别方法的发展  

Development of wavelet-transform-based power quality disturbance detection and identification

作　　者：张秀娟[1] 徐永海[1] 肖湘宁[1] 

机构地区：[1]华北电力大学电力工程系,北京102206

出　　处：《电力自动化设备》2003年第9期67-71,共5页Electric Power Automation Equipment

基　　金：高等学校博士学科点专项科研基金资助项目(20010079002)~~

摘　　要：电能质量扰动问题近年来已经成为众多领域关注的焦点,国内外学者提出了一系列对电能质量扰动进行分析的方法。介绍几种常用的电能质量扰动检测和识别方法,重点分析了基于小波变换以及小波变换与其他方法如时域分析法、d-q变换、人工神经网络等相结合的电能质量扰动识别方法,比较了各种方法的特点,指出了该领域研究发展的前景。In recent years,power quality disturbance has been concerned in many fields.Many me -thods to analyze this proble m have been put forward now.Several approaches commonly used to detect and identify the disturbances are presented.The wavelet-transform-based methods and its combination with other arithmetic,such as time-domain analysis,d-q conversion,artificial neural net-work etc.,are focused on.The performance comparisons are made among these approaches,including merits and defects.The study prospect of power quality disturbance detection and identification is given.

关 键 词：电能质量 扰动检测与识别 小波变换 奇异性 

分 类 号：TM761[电气工程—电力系统及自动化]