引用本文:房国志,胡兵方,宋国义.电网中3类典型扰动信号的检测方法[J].电力自动化设备,2008,(6):
.Detection of three typical disturbances in power system[J].Electric Power Automation Equipment,2008,(6):
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电网中3类典型扰动信号的检测方法
房国志,胡兵方,宋国义
作者单位
摘要:
对小波分析技术在电力系统3类典型扰动信号(电压下凹、电压冲击、暂态高频振荡)识别的应用进行研究的基础上,针对目前所采用小波基对扰动信号进行定位时存在较大误差的特点,提出了运用具有无限可导性、双正交性和无频谱混叠的Meyer小波基函数对3类扰动进行小波分解,进而进行准确识别定位的新方法。对3类典型扰动信号运用该方法进行仿真试验,并将暂态高频振荡信号的分析结果与用db5小波基分析结果进行了比较,结果表明该方法具有更高的准确性。
关键词:  电能质量,小波分析,Meyer函数,畸变信号,随机过程
DOI:
分类号:TM711
基金项目:
Detection of three typical disturbances in power system
FANG Guozhi  HU Bingfang  SONG Guoyi
Abstract:
The applications of wavelet analysis technique in the detection of three typical power system disturbances(voltage sag,voltage impulse and high - frequency transient oscillation) are analyzed,which shows that the orientation precision is insufficient.A detection method is presented,which applies a mother wavelet basis function(Meyer) with infinite differentiability,biorthogonality and non-overlapping frequency bands to identify the occurrence and duration of disturbances.Simulative test is carried out for three typical power system disturbances.Its detection result for transient high frequency oscillation is compared with that of db5 analysis,which shows this method has higher accuracy.
Key words:  power quality,wavelet analysis,Meyer function,distorted signal,stochastic process

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