基于阻抗偏差最小判据和改进自适应蝙蝠算法的系统侧谐波阻抗估计方法

针对已有的系统侧谐波阻抗估计方法对背景谐波波动敏感的问题，提出了一种新的系统侧谐波阻抗估计方法。根据阻抗偏差最小判据和改进自适应蝙蝠算法寻优得到最优系统侧谐波阻抗初值，以得到与真实值相近的背景谐波电压估计值。对背景谐波电压估计值进行K-means聚类分析，并依据聚类结果将谐波样本数据分成多簇，使得每簇数据对应的背景谐波波动减少。考虑到谐波数据均为复数相量，采用复最小二乘法分别求取各簇数据的系统侧谐波阻抗估计值，并将其均值作为最终估计值。与已有的方法相比，所提方法更能适应背景谐波波动的变化，且在用户侧谐波阻抗非远大于系统侧谐波阻抗的场景下具有更好的估计精度。多个算例分析结果验证了所提方法的有效性和适用性。

System-side harmonic impedance estimation method based on minimum impedance deviation criterion and improved adaptive bat algorithm

Aiming at the problem that the existing system-side harmonic impedance estimation methods are sensitive to the background harmonic fluctuation, a novel system-side harmonic impedance estimation method is proposed. Based on the minimum impedance deviation criterion and the improved adaptive bat algorithm, the optimal initial value of the system-side harmonic impedance is obtained, so as to get the estimation value of background harmonic voltage which is close to the real value. K-means cluster analysis is carried out on the estimation value of background harmonic voltage, and based on the clustering results the harmonic sample data is divided into multiple clusters, so that the background harmonic fluctuation corresponding to each cluster data is reduced. Considering that the harmonic data are all complex phasors, the complex least square method is used to obtain the estimation value of system-side harmonic impedance in each cluster, and the mean value of them is taken as the final estimation value. Compared with the existing methods, the proposed method can better adapt to the change of background harmonic fluctuation, and has better estimation accuracy when the user-side harmonic impedance is not much greater than the system-side harmonic impedance. Several examples verify the effectiveness and applicability of the proposed method.