基于无迹粒子滤波的电网动态谐波估计

发布时间：2018-07-05 00:47

本文选题：电力系统 + 电能质量　；参考：《深圳大学学报(理工版)》2016年01期

【摘要】：提出一种基于无迹粒子滤波(unscented particle filter,UPF)算法的电网动态谐波估计方法.通过无迹卡尔曼滤波算法得到电网动态谐波状态量的估计值和协方差,运用这些结果改进传统粒子滤波算法的重要密度函数,采用粒子滤波算法得到电网动态谐波的最优估计值.该方法克服了无迹卡尔曼滤波算法(unscented Kalman filter,UKF)对噪声要求为高斯分布的限制和传统粒子滤波(particle filter,PF)算法易退化的缺点,保留了UKF对非线性问题的较好处理和PF强抗干扰性能力.仿真结果表明,在高斯噪声和非高斯噪声情况下,UPF算法得到的电网动态谐波幅值、相位的估计值都更接近真实值.
[Abstract]:A dynamic harmonic estimation method based on unscented particle filter (unscented particle filter) algorithm is proposed. The estimation value and covariance of dynamic harmonic state of power network are obtained by unscented Kalman filter algorithm. The important density function of traditional particle filter algorithm is improved by using these results. The particle filter algorithm is used to obtain the optimal estimation value of power grid dynamic harmonics. This method overcomes the limitation of unscented Kalman filter which requires the noise to be Gao Si distribution, and the traditional particle filter (particle filter) algorithm is easy to degenerate, which preserves the better handling of nonlinear problems and the strong anti-interference ability of PF. The simulation results show that the phase estimation of the dynamic harmonic amplitude obtained by the Gao Si algorithm is closer to the real value under both the Gao Si noise and the non-Gao Si noise.
【作者单位】：深圳大学光电工程学院;深圳大学机电与控制工程学院;
【基金】：国家自然科学基金资助项目(51477104) 深圳市基础研究计划资助项目(JCYJ20140418193546100)~~
【分类号】：TN713;TM714.2

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