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Fast recursive Gauss-Newton adaptive filter for the estimation of power system frequency and harmonics in a noisy environment

机译:快速递归高斯-牛顿自适应滤波器,用于估计嘈杂环境中的电力系统频率和谐波

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摘要

This study presents a new recursive Gauss??Newton method-based adaptive filter for estimating the time-varying amplitude, phase, and frequency of fundamental and harmonic components of power system voltage or current corrupted by noise. The coefficients of the adaptive filter are obtained from unconstrained optimisation of an error function weighted by a variable forgetting factor, and using suitable approximation of the recursive Gauss??Newton algorithm for reducing computational complexity. To improve the tracking speed and accuracy of the filter, the forgetting factor is tuned iteratively. This approach is very much suitable for a large variety of applications in the distributed generation control and protection, synchronised phasor measurement of voltage and current signals using phasor measurement units, power electronic converters etc. Several computational issues like the time-varying nature of the power system voltage and frequency parameters, noise and distortion, presence of decaying dc and inter-harmonics are considered to evaluate the fast operation and robustness of the proposed approach.
机译:这项研究提出了一种基于递归高斯牛顿法的自适应滤波器,用于估计电力系统电压或电流被噪声破坏后的基波和谐波分量的时变幅度,相位和频率。自适应滤波器的系数是通过对误差函数的无约束优化(由变量遗忘因子加权)获得的,并使用递归的高斯牛顿算法的适当近似值来降低计算复杂性。为了提高滤波器的跟踪速度和精度,可以对遗忘因子进行迭代调整。这种方法非常适用于分布式发电控制和保护,使用相量测量单元,电力电子转换器等对电压和电流信号进行同步相量测量的各种应用。一些计算问题,例如电源的时变特性系统电压和频率参数,噪声和失真,衰减的直流电和谐波之间的存在被认为可以评估该方法的快速运行和鲁棒性。

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