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A Self-Adaptive Contractive Algorithm for Enhanced Dynamic Phasor Estimation

机译:一种自适应收缩算法,用于增强动态相位估计

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In this paper, a self-adaptive contractive (SAC) algorithm is proposed for enhanced dynamic phasor estimation in the diverse operating conditions of modern power systems. At a high-level, the method is composed of three stages: parameter shifting, filtering and parameter unshifting. The goal of the first stage is to transform the input signal phasor so that it is approximately mapped to nominal conditions. The second stage provides estimates of the phasor, frequency, rate of change of frequency (ROCOF), damping and rate of change of damping (ROCOD) of the parameter shifted phasor by using a differentiator filter bank (DFB). The final stage recovers the original signal phasor parameters while rejecting misleading estimates. The most important features of the algorithm are that it offers convergence guarantees in a set of desired conditions, and also great harmonic rejection. Numerical examples, including the IEEE C37.118.1 standard tests with realistic noise levels, as well as fault conditions, validate the proposed algorithm.
机译:本文提出了一种自适应收缩(SAC)算法,用于增强现代电力系统各种操作条件中的动态相位估计。在高级别,该方法由三个阶段组成:参数转换,过滤和参数脱模。第一阶段的目标是转换输入信号相量,使其大致映射到名义条件。通过使用鉴别器滤波器组(DFB),第二阶段提供相分机,频率,频率变化率,频率变化(Rocof)的变化率,阻尼(Rocod)的变化(Rocod)的变化率,阻尼(Rocod)。最终阶段在拒绝误导性估计的同时恢复原始信号量相参数。该算法的最重要的特征是它在一组所需条件下提供收敛保证,并且也具有大的谐波抑制。数值示例,包括具有现实噪声水平的IEEE C37.118.1标准测试,以及故障条件,验证所提出的算法。

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