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.
出处
《电力自动化设备》
EI
CSCD
北大核心
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)~~
关键词
电能质量
扰动检测与识别
小波变换
奇异性
power quality
disturbance detection and identification
wavelet transform
singularity
