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首页> 外文期刊>IEEE Transactions on Power Delivery >A Modified Empirical Mode Decomposition Filtering-Based Adaptive Phasor Estimation Algorithm for Removal of Exponentially Decaying DC Offset
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A Modified Empirical Mode Decomposition Filtering-Based Adaptive Phasor Estimation Algorithm for Removal of Exponentially Decaying DC Offset

机译:改进的基于经验模式分解滤波的自适应相量估计算法,用于去除指数衰减的直流偏移

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摘要

This paper proposes a modified empirical-mode decomposition (EMD) filtering-based adaptive dynamic phasor estimation algorithm for the removal of exponentially decaying dc offset. Discrete Fourier transform does not have the ability to attain the accurate phasor of the fundamental frequency component in digital protective relays under dynamic system fault conditions because the characteristic of exponentially decaying dc offset is not consistent. EMD is a fully data-driven, not model-based, adaptive filtering procedure for extracting signal components. But the original EMD technique has high computational complexity and requires a large data series. In this paper, a short data series-based EMD filtering procedure is proposed and an optimum hermite polynomial fitting (OHPF) method is used in this modified procedure. The proposed filtering technique has high accuracy and convergent speed, and is greatly appropriate for relay applications. This paper illustrates the characteristics of the proposed technique and evaluates its performance by computer-simulated signals, PSCAD/EMTDC-generated signals, and real power system fault signals.
机译:提出了一种改进的基于经验模式分解(EMD)滤波的自适应动态相量估计算法,用于去除指数衰减的直流偏移。离散傅立叶变换无法在动态系统故障条件下获得数字保护继电器中基本频率分量的精确相量,因为直流衰减的指数衰减特性不一致。 EMD是一种完全数据驱动的,不是基于模型的自适应滤波程序,用于提取信号分量。但是原始的EMD技术具有很高的计算复杂度,并且需要大量的数据序列。本文提出了一种基于短数据序列的EMD滤波程序,并在此修改程序中使用了最佳厄米多项式拟合(OHPF)方法。所提出的滤波技术具有较高的精度和收敛速度,非常适合于中继应用。本文阐述了所提出技术的特性,并通过计算机仿真信号,PSCAD / EMTDC生成的信号以及实际电力系统故障信号来评估其性能。

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