基于调制分量卡尔曼滤波的短时扰动检测

提出了一种基于调制分量的低阶卡尔曼滤波模型．实时检测电能质量短时扰动。该方法将三相电压信号的αβ变换结果分解为基波信号和调制信号．提取调制信号的两个特征分量作为新的状态变量，避免了单独设置各次谐波为状态变量，降低模型阶次并提高暂态响应速度。根据暂态时滤波误差发生突变的特征，提出误差比阈值法判断暂态过程的起止时间。通过自适应修正系统噪声方差阵Q．降低模型误差并有效抑制滤波发散现象。Matlab仿真结果表明所提方法比普通卡尔曼滤波和低通滤波器具有更高的稳态精度和更快的暂态响应速度。

Short-Term Disturbance Detection Based on Modulation Kalman Filter

A low-order Kalman filter model based on modulation is presented to detect real-time disturbances of short-term power quality, αβ transform result of three-phase voltage is decomposed into the fundamental signal and modulation signal. Then two characteristics of modulation signal replacing each harmonic are taken as new state variables. It reduces model orders and improves speed of transient response. Considering the characteristic of filtering error which occur mutation when there is a transient signal, the method of filtering error ratio threshold is introduced to judge initiative and terminative time of transient. Then system noise matrix Q is adapted automatically in order to reduce model error and restrain radiation. Simulation results of Matlab show that the new method has higher accuracy of steady-state and faster speed of transient response than general Kalman filters and low-pass filters.