小波包变换在电能质量扰动检测中的应用

鉴于小波包变换能够均匀划分信号频带,聚焦任意频率,是暂态电能质量扰动分析的良好工具,提出了在噪声环境中电能质量扰动检测和定位的有效方法,即利用小波包变化模极大值原理定位电力系统短时扰动并确定扰动持续时间。仿真表明,通过小波包一、二次分解和重构能更好地提取扰动特征信息,从而为电能质量的检测、评估及治理提供依据,且该算法计算简单、快速、有效。

Application of Wavelet Package Transform in Power Quality Disturbance Detection

Wavelet package can uniformly divide the signal frequency into sub bands and can focus on any frequency.It is a good tool for transient power quality disturbances detection and localization.The detection and location of the start point and end point of the voltage sag and swell is a key problem for the power quality monitoring.An effective method containing noise detection and location of power quality disturbance is proposed under noise environment.By use of wavelet package transform module maximum the short-time disturbances of power system are detected and the durations of disturbances are determined.By resolving wavelet package once or two times and rebuilding,the characteristic information of disturbances can be well extracted.The Matlab simulation demonstrates that it is also able to extract signal of the power quality disturbance very effectively when there is serious disturbance by Gaussian white noise.When the signal to noise ratio is 3db,by use of wavelet package two times resolving and anew buildup(by use of wavelet package transform module maximum for continuous two times),the power quality disturbances such as voltage sag and swell is precisely detected and located.Thus the basis for detection,evaluation and harnessing of power quality is provided.The algorithm is simple and quick.Simulation results show its effectiveness.Therefore it is especially suitable for detecting weak signal from seriously disturbed signal.