Abstract

A two-stage algorithm is proposed for the estimation of the fundamental frequency of asynchronously sampled signals in power systems. In the first stage, time-domain interpolation reconstructs the power system signal at a new sampling time and the reconstructed signal passes through a tuned sine filter to eliminate harmonics. In the second stage, the fundamental frequency is estimated using a modified curve fitting, which is robust to noise. The evaluation results confirm the efficiency and validity of the two-stage algorithm for accurate estimation of the fundamental frequency even for asynchronously sampled signals contaminated with noise, harmonics, and an inter-harmonic component.

Highlights

  • Sampling-based power measurements are typically carried out using a clock signal that is synchronized with the signal from the power system under analysis

  • This paper proposes a tuned sine filter that adjusts its reference frequency to synchronize with an estimate of the fundamental frequency

  • A two-stage algorithm is proposed for estimation of the fundamental frequency of asynchronously sampled signals in power systems

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Summary

Introduction

Sampling-based power measurements are typically carried out using a clock signal that is synchronized with the signal from the power system under analysis. Energies 2015, 8 industrial measurements and high-precision calibrations in metrology laboratories Under such circumstances, accurate estimation of the fundamental frequency of power system signals is essential to minimize the errors caused by asynchronous sampling. The 4PSF algorithm is more suited to less distorted steady-state waveforms, since its performance significantly degrades as total harmonic distortion (THD) increases Parametric interpolations, such as cubic spline interpolations [20,21] and Newton interpolations [22,23], offer an alternative time-domain approach and are used to modify the sampling rate of an analog-to-digital conversion in software. A two-stage algorithm is proposed for accurate estimation of the fundamental frequency of asynchronously sampled signals regardless of noise and harmonics.

Two-Stage Algorithm for Estimating a Fundamental Frequency
Tuned Sine Filtering Followed by Time-Domain Interpolation
Modified Curve Fitting with an Unknown Frequency
Frequency Estimation Procedure
Number of Cycles in the Data Window
Noise Level
Fluctuating Harmonic Component
Fluctuating Inter-Harmonic Component
Computational Burden
Hardware Implementation
Conclusions
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