When the voltage and current signals measured in ac power systems are highly distorted due to high penetration of nonlinear loads and power electronics converters (e.g., in microgrids) and measurement noise, the traditional methods of frequency calculation will be associated with a significant error. This article introduces a novel power frequency estimation method based on a Bayesian online changepoint detector. In each time step of this method, the most efficient changepoints are detected in a window containing the latest measured voltage samples. The frequency is estimated and updated after applying some refining procedures on these changepoints. The results of numerical studies on various simulated and laboratory-generated signals under standard and severe conditions confirm that the suggested method can estimate the frequency accurately and robustly in dealing with frequency deviations, harmonics, interharmonics, dc components, noise, nonideal sampling, amplitude and phase angle modulations, and step variations. For instance, the proposed method can tolerate high noise levels and remain robust even at a signal-to-noise ratio of 20 dB, achieving mean absolute errors of 0.036 Hz without prefiltering and 0.004 Hz with prefiltering. It can also exhibit an invariant response to significant step variations in the voltage amplitude and phase angle.

中文翻译：

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基于贝叶斯在线变点检测器的工频估计


当交流电力系统中测量的电压和电流信号由于非线性负载和电力电子转换器（例如在微电网中）的高渗透以及测量噪声而高度失真时，传统的频率计算方法将产生显着的误差。本文介绍了一种基于贝叶斯在线变点检测器的新型工频估计方法。在此方法的每个时间步长中，在包含最新测量电压样本的窗口中检测最有效的变化点。在对这些变化点应用一些细化程序后，估计和更新频率。对标准和恶劣条件下各种模拟和实验室生成信号的数值研究结果证实，所提出的方法可以准确、鲁棒地估计频率，以处理频率偏差、谐波、间谐波、直流分量、噪声、非理想采样、幅度和相位角调制和阶跃变化。例如，所提出的方法可以容忍高噪声水平，即使在 20 dB 的信噪比下也能保持鲁棒性，在没有预滤波的情况下实现 0.036 Hz 的平均绝对误差，在有预滤波的情况下实现 0.004 Hz 的平均绝对误差。它还可以对电压幅度和相位角的显着阶跃变化表现出不变的响应。