With the development of smart grid, a lot of nonlinear loads and new energy power stations are connected into the power network. There are a large number of harmonic sources in the power grid, harmonic distortion has become one of the main power quality concerns in recent years. Utility side harmonic impedance estimation is important for evaluating harmonic emission levels and determining the harmonic responsibility. In the traditional methods, the harmonic voltage and current at the PCC are considered to satisfy the normal distribution and the timing correlation of them is ignored which contains important information that can be used to estimate the harmonic impedance. This paper proposes a new method for harmonic impedance estimation based on the Burg algorithm and AR model. In this paper, harmonic voltage and current are considered to satisfy AR model including timing correlation. The reflection coefficient is calculated by minimizing the average power of the forward and backward errors in the AR model. Then, the utility side harmonic impedance is estimated by minimizing the apparent power. The proposed method is robust, and the error of the estimation result is small by the proposed method. Whats more, the proposed method is not limited by some traditional assumptions, such as the background harmonics are stable and small, the customer harmonic impedance is much larger than the utility, and the harmonic sources of both sides are independent, and so on.

随着智能电网的发展，大量非线性负载和新能源电站接入电网。电网中存在大量谐波源，谐波畸变已成为近年来主要的电能质量问题之一。公用事业侧谐波阻抗估计对于评估谐波发射水平和确定谐波责任很重要。在传统方法中，PCC 处的谐波电压和电流被认为满足正态分布，而忽略它们的时序相关性，其中包含可用于估计谐波阻抗的重要信息。本文提出了一种基于Burg算法和AR模型的谐波阻抗估计新方法。在本文中，谐波电压和电流被认为满足包含时序相关性的 AR 模型。通过最小化 AR 模型中前向和后向误差的平均功率来计算反射系数。然后，通过最小化视在功率来估计公用事业侧谐波阻抗。该方法具有鲁棒性，估计结果的误差较小。更重要的是，所提出的方法不受一些传统假设的限制，例如背景谐波稳定且较小、用户谐波阻抗远大于市电、两侧谐波源独立等。通过最小化视在功率来估计公用事业侧谐波阻抗。该方法具有鲁棒性，估计结果的误差较小。更重要的是，所提出的方法不受一些传统假设的限制，例如背景谐波稳定且较小、用户谐波阻抗远大于市电、两侧谐波源独立等。通过最小化视在功率来估计公用事业侧谐波阻抗。该方法具有鲁棒性，估计结果的误差较小。更重要的是，所提出的方法不受一些传统假设的限制，例如背景谐波稳定且较小、用户谐波阻抗远大于市电、两侧谐波源独立等。