一种基于卡尔曼滤波的电能质量扰动检测新方法

发布时间：2018-01-04 18:12

本文关键词：一种基于卡尔曼滤波的电能质量扰动检测新方法　出处：《中国电机工程学报》2017年22期 　论文类型：期刊论文

【摘要】：基于正弦波/指数函数自相关的运动状态估计模型,提出一种基于卡尔曼滤波(Kalman filter,KF)的电能质量扰动(power quality disturbances,PQD)检测方法(KFPQD检测方法)。提出方法针对基波频率的纯正弦电压信号模型,以及基波频率纯正弦信号叠加指数衰减的电流信号模型,选取电压信号及其一阶导数形成二维电压状态向量,选取电流信号及其一阶导数、衰减直流分量形成三维电流状态向量,进行状态空间建模,离散化后采用KF算法对电压/电流及其变化率进行状态估计,跟踪检测基波电压/电流信号的跳变。仿真和微电网PQD检测实验结果表明:提出方法在跟踪精度、抗干扰性和敏感性方面均优于传统KFPQD方法,提高对电压与电流跳变的跟踪性能。
[Abstract]:Based on the motion state estimation model of sine wave / exponential function autocorrelation, a Kalman filter based on Kalman filter is proposed. Power quality disturbances. This paper presents a pure sinusoidal voltage signal model for the fundamental frequency and a current signal model for the exponential attenuation of the pure sinusoidal signal of the fundamental frequency. Selecting voltage signal and its first derivative to form two-dimensional voltage state vector, selecting current signal and its first derivative, attenuating DC component to form three-dimensional current state vector, and modeling state space. After discretization, KF algorithm is used to estimate the state of voltage / current and its rate of change. The simulation and PQD test results show that the proposed method is superior to the traditional KFPQD method in tracking accuracy, anti-jamming and sensitivity. Improved tracking performance for voltage and current jumps.
【作者单位】：南昌大学信息工程学院;
【基金】：国家自然科学基金项目(51467013)~~
【分类号】：TM930
【正文快照】： 度、抗干扰性和敏感性方面均优于传统KFPQD方法,提高对电压与电流跳变的跟踪性能。0引言电能质量扰动(power quality disturbances,PQD)检测是电能质量治理关键技术之一。用于PQD检测的方法很多,包括快速傅里叶变换(fastFourier transform,FFT)、短时傅里叶变换、小波变换、希

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