基于自适应容积卡尔曼滤波的动态谐波检测

对电网中的谐波进行实时、准确的检测是有效治理谐波的前提。针对某些运行工况下电网中出现的动态谐波，提出了一种基于自适应容积卡尔曼滤波的动态谐波检测算法估计谐波信号的幅值和相角。首先针对传统卡尔曼滤波处理非线性关系上的局限性，利用容积卡尔曼滤波不需要任何线性化关系的特性估计谐波的状态向量和误差偏差矩阵，然后引入噪声估值遗忘因子来实时更新系统的噪声矩阵方程。最后通过对比实验，验证了该算法在动态谐波检测上的优越性能，并将其应用于有源滤波器的谐波检测中。

Dynamic Harmonic Detection Based on Adaptive Cubature Kalman Filter

The real-time and accurate detection of harmonics in power grid is a prerequisite for effective harmonic suppression. For the dynamic harmonics appearing in the power grid under certain operating conditions， this paper proposes an adaptive cubature Kalman filter-based dynamic harmonic detection algorithm to estimate the amplitude and phase angle of harmonic signals. Firstly， to address the limitations of the conventional Kalman filter in dealing with nonlinear relations， the state vector and error deviation matrix of the harmonics are estimated by using the property of the cubature Kalman filter that does not require any linearization relations. Then a noise estimation forgetting factor is introduced to update the noise matrix equation of the system in real time. Finally， the superior performance of the algorithm in the dynamic harmonic detection is verified through comparative experiments， and the algorithm is applied to the harmonic detection of active filters.