Frequency Shifting And Filtering Algorithm for Power System Harmonic Estimation

Zhang, Junhao; Wen, He; Tang, Lu; Teng, Zhaosheng; Zhou, C.

doi:10.1109/amps.2017.8078329

Cited by 8 publications

(6 citation statements)

References 16 publications

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“…Applying FSF to estimate the power system frequency as shown in [11] requires the following 6 steps. STEP 1, acquiring the power system signal distorted by harmonic content with sampling frequency fs as:…”

Section: Frequency Estimation Based On Fsfmentioning

confidence: 99%

“…In this section, the influence of the AWGN on power frequency estimation provided by FSF [11] is investigated. The variance expression of the power frequency estimation based on FSF is analyzed and derived theoretically.…”

Section: Analysis Of White Noise On the Power Frequency Estimationmentioning

confidence: 99%

“…To improve the performance of DFT, an effective method named Frequency Shifting and Filtering (FSF) algorithm is proposed to estimate the frequency [11]. The FSF only employs two main steps, by starting from the raw data: frequency shifting by the reference signal (similar to the heterodyne action of WIFFT) and iterative filtering (similar to the windowing action of WIFFT) based on the averaging filter, to process the raw data.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of White Noise on Power Frequency Estimation by DFT-Based Frequency Shifting and Filtering Algorithm

Zhang

Tang

Mingotti

et al. 2020

IEEE Trans. Instrum. Meas.

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The frequency shifting and filtering (FSF) algorithm, a variant of DFT, has the merit of high efficiency for frequency analysis thanks to its simple implementation in the time domain. However, the inevitable white noise injected by various factors leads to inaccurate frequency estimation in practical measurement. This paper investigates the influence of a stationary white noise on FSF-based frequency estimation of the power system. The variance expression of the frequency estimator is derived theoretically and compared to its unbiased Cramer-Rao Lower Bound (CRLB). The obtained results are validated by several computer simulations.

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Section: Frequency Estimation Based On Fsfmentioning

confidence: 99%

Section: Analysis Of White Noise On the Power Frequency Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysis of White Noise on Power Frequency Estimation by DFT-Based Frequency Shifting and Filtering Algorithm

Zhang

Tang

Mingotti

et al. 2020

IEEE Trans. Instrum. Meas.

Self Cite

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show abstract

“…As for the deduction of FSF-based phase variance, the variance of η(n) is firstly obtained according to (12) as:…”

Section: A Derivation Of the Variance Expressionsmentioning

confidence: 99%

“…The Frequency Shifting and Filtering algorithm (FSF), a Noise Analysis on Frequency Shifting and Filtering Algorithm-Based Phasor Estimator variant of DFT, estimates the frequency, amplitude, and phase of the power systems only by three steps in time domain: first, shifting the negative fundamental frequency of the sampled signal by reference signal; then, the frequency shifted signal is filtered by the iterative filtering process based on the averaging filter; finally, the parameters of the power system signal are estimated by two filtered samples [12]. In [13], the accuracy of FSF on harmonic estimation is analysed, moreover, the computational burden of FSF is reduced by using the proposed Equivalent Weighting Filter (EWF).…”

mentioning

confidence: 99%