人工智能和数学变换用于电能质量的研究综述

由于故障、动态运行和非线性负荷的加入,使动态电能质量问题越来越复杂,因此电能质量的问题重新受到关注。特别是随着小波理论自身的发展和世界范围内小波分析算法研究热潮的兴起,以及各种人工智能技术在电力系统的成功应用,对动态电能质量扰动的起因和来源有了很好的理解,对动态电能质量的识别、检测、分类和统计有了很好的解决办法。为了在现有研究成果的基础上,进一步对动态电能质量进行研究,明确尚需进行的工作,在大量查阅各种国际会议、学术刊物上发表的电能质量论文后,综述了近年来人工智能和傅立叶变换、短窗傅立叶变换和小波变换在电

A summary of AI & mathematics transform applied to power quality study

In the past decades, faults, dynamic operations and nonlinear loads together made the dynamic power quality more and more complex.Thereby,more interest has been laid in power quality.With the development of wavelet theory, worldwide spread of the study on wavelet algorithm and the successful applications of various AI techniques to power system, the causes and origins of dynamic power quality have got a better comprehension. Meanwhile,the methods of the identification,detection,classification and statistics of power quality have been greatly advanced.In order to propel the further study on the power quality and make the researches needed to be done clear,the main achievements and methods of power quality study,i.e.AI, Fourier transform, Short-time Fourier transform, Wavelet transform, are surveyed in this paper after consulting lots of PQ thesises in international conferences and science periodicals. Literature also presents certain problems to be solved.