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作 者:龚静 GONG Jing(School of Electrical and Information Engineering,Beijing Key Laboratory of Intelligent Processing for Building Big Data,Beijing University of Civil Engineering and Architecture,Beijing 100044)
机构地区:[1]北京建筑大学电气与信息工程学院建筑大数据智能处理方法研究北京市重点实验室,北京100044
出 处:《北京建筑大学学报》2023年第5期108-114,共7页Journal of Beijing University of Civil Engineering and Architecture
基 金:国家公派留学基金项目(201809960015);北京市属高校基本科研业务费项目(X20075)。
摘 要:对电能扰动的准确检测是治理改善电能质量的重要前提。首先分析了复小波变换,其能提供2个正交空间中信号分量间特有的相角信息,选取shan2-2为母小波,确定采样频率6400 Hz,随之提出了一种基于复小波变换相角差值的扰动检测方法,即分别对基准正弦波形和扰动波形进行复小波变换,求出对应的相角差值,以此信息数组中零值数目作为扰动起止时刻检测和扰动类型判断的依据,给出详细的流程框图和实用判据。针对电压暂降、暂升、中断、脉冲4种典型暂态扰动进行仿真验证,结果表明:本方法较复小波模值判断和实数小波检测更准确,抗干扰的能力更强。The accurate detection of power disturbance is an important prerequisite for improving power quality.The complex wavelet transform is analyzed,which can provide the unique phase angle information between the signal components in two orthogonal spaces.Shan2-2 is selected as the mother wavelet,and the sampling frequency is 6400 Hz.Then a disturbance detection method based on the phase angle difference of the complex wavelet transform is proposed,that is,the complex wavelet transform is carried out on the reference sine waveform and the disturbance waveform respectively,and the corresponding phase angle difference is obtained.The number of zero values in the information array is used as the basis for the detection of disturbance time and the judgment of disturbance type.The detailed flow chart and practical criteria are given in this paper.Simulation experiments are carried out for four typical transient disturbances:voltage sag,rise,interruption and pulse.The results show that this method is more accurate than complex wavelet modulus judgment and real wavelet detection,and has stronger anti-interference ability.
分 类 号:TM930.12[电气工程—电力电子与电力传动]
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