基于WAMS的电网扰动辨识与应用

WAMS Based Power Network Disturbance Identification and Application

及时获悉电网扰动发生的时间、地点对于帮助运行人员有针对性地采取控制措施,及时消除扰动,保障电网安全稳定运行具有重要意义。本文利用小波多分辨率分析作为分析工具,根据小波系数(wavelet coefficient,WC)的能量选择恰当的小波函数和分解尺度,对广域测量系统(wide-area measurement system,WAMS)记录的频率信号进行时频域分解,利用得到的最大小波系数作为扰动辨识指标,以实现对扰动的在线辨识。10机39节点系统仿真说明了所提方法的应用过程和效果。基于该方法研制了电网扰动源在线辨识系统,实测的电网扰动数据进一步验证了所提方法和系统的有效性和可行性。

Identifying disturbances timely and accurately is greatly helpful to take proper anticipatory actions to eliminate the disturb- ances and avoid blackouts. In this paper, the wavelet multi-resolution analysis based method is proposed to identify power system dis- turbances. The energy of wavelet coefficients is used as a criterion to choose optimal wavelet function and decomposition scale, which are used for obtaining the maximum wavelet coefficients by identifying the frequency signals from wide area measurement system （WAMS）. The maximum wavelet coefficients are then selected to be the indicators for disturbance identifying. The detailed procedure and effectiveness of the proposed method is demonstrated by simulations of a 10-machine 39-bus system. A software system has been developed for an actual power system based on the method and the measured disturbances to validate the effectiveness and feasibility of the method and software.