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Choosing The Optimum Frequency Estimator Under System Frequency Deviations In Power Systems

Year 2021, Issue: 27, 670 - 675, 30.11.2021
https://doi.org/10.31590/ejosat.904157

Abstract

Parameter estimation in particular the frequency estimation of sinusoidal signals contaminated with noise is of great importance due to its broad applications in many fields such as communications, instrumentation, medicine and radar. In today’s power systems, frequency deviations in the nominal system frequency would cause spurious or so-called ghost frequency components in the spectrum. Those types of frequency components complicate the real-time tracking of harmonics and interharmonics present in the system. In this study, in order to minimize the side effects of system frequency deviations the performances of various frequency estimators are evaluated against varying fundamental frequency and noise conditions and the optimum estimator is chosen.

Thanks

The authors would like to thank Prof. O. Salor-Durna, Department of Electrical and Electronics Engineering, Gazi University, Ankara, Turkey for providing field data used in the experimental work.

References

  • Kay, S. M. (1988). Modern spectral estimation: theory and application. Pearson Education India.
  • Slepian, D. (1954). Estimation of signal parameters in the presence of noise. Transactions of the IRE Professional Group on Information Theory, 3(3), 68-89.
  • Palmer, L. (1974). Coarse frequency estimation using the discrete Fourier transform (Corresp.). IEEE Transactions on Information Theory, 20(1), 104-109.
  • Rife, D. C. B. P., & Boorstyn, R. (1974). Single tone parameter estimation from discrete-time observations. IEEE Transactions on information theory, 20(5), 591-598.
  • Quinn, B. G. (1994). Estimating frequency by interpolation using Fourier coefficients. IEEE transactions on Signal Processing, 42(5), 1264-1268.
  • Quinn, B. G. (1997). Estimation of frequency, amplitude, and phase from the DFT of a time series. IEEE transactions on Signal Processing, 45(3), 814-817.
  • Macleod, M. D. (1998). Fast nearly ML estimation of the parameters of real or complex single tones or resolved multiple tones. IEEE Transactions on Signal processing, 46(1), 141-148.
  • Jacobsen, E., & Kootsookos, P. (2007). Fast, accurate frequency estimators [DSP Tips & Tricks]. IEEE Signal Processing Magazine, 24(3), 123-125.
  • Candan, Ç. (2013). Analysis and further improvement of fine resolution frequency estimation method from three DFT samples. IEEE Signal Processing Letters, 20(9), 913-916.
  • Salor, Ö. (2009). Spectral correction-based method for interharmonics analysis of power signals with fundamental frequency deviation. Electric power systems research, 79(7), 1025-1031.
  • Kalair, A., Abas, N., Kalair, A. R., Saleem, Z., & Khan, N. (2017). Review of harmonic analysis, modeling and mitigation techniques. Renewable and Sustainable Energy Reviews, 78, 1152-1187.
  • Akdağ, O , Yeroğlu, C . (2018). 154 kV İletim Hatlarındaki Akım Transformatörlerinde Simülasyon Modeli ile Harmonik Bozulmaya Dayalı Doygunluk Algılama Yöntemi . Avrupa Bilim ve Teknoloji Dergisi , (14) , 353-363.
  • Fidan, P , Akdemir, H , Kekezoğlu, B , Adiyıl, İ . (2018). İstanbul’da Bir Raylı Sistem Tesisi’ne Ait Harmonik Analizi ve Çözüm Önerileri . Avrupa Bilim ve Teknoloji Dergisi , (14) , 215-221.
  • Gökozan, H . (2021). The Effect of an Induction Heating System on Power Quality Parameters . Avrupa Bilim ve Teknoloji Dergisi , (21) , 25-30.
  • Compatibility, E. General Guide on Harmonics and Interharmonics Measurements and Instrumentation. IEC Standard, 61000-4.
  • Lin, H. C. (2011). Power harmonics and interharmonics measurement using recursive group-harmonic power minimizing algorithm. IEEE Transactions on Industrial Electronics, 59(2), 1184-1193.

Güç Sistemlerinde Sistem Frekans Kayması Olduğu Durumlarda En Uygun Frekans Kestirici Seçimi

Year 2021, Issue: 27, 670 - 675, 30.11.2021
https://doi.org/10.31590/ejosat.904157

Abstract

Parametre tahmini, özellikle gürültü ile kirlenmiş sinüzoidal sinyallerin frekans tahmini, iletişim, enstrümantasyon, tıp ve radar gibi birçok alandaki geniş uygulamaları nedeniyle büyük önem taşımaktadır. Günümüzün güç sistemlerinde, nominal sistem frekansındaki frekans sapmaları, spektrumda sahte veya sözde hayalet frekans bileşenlerine neden olmaktadır. Bu tür frekans bileşenleri, sistemde bulunan harmoniklerin ve araharmoniklerin gerçek zamanlı izlenmesini zorlaştırmaktadır. Bu çalışmada, sistem frekans sapmalarının yan etkilerini en aza indirmek için, çeşitli frekans kestiricilerin performansları, değişen temel frekans ve gürültü koşullarına göre değerlendirilmiş ve en uygun kestirici seçilmiştir.

References

  • Kay, S. M. (1988). Modern spectral estimation: theory and application. Pearson Education India.
  • Slepian, D. (1954). Estimation of signal parameters in the presence of noise. Transactions of the IRE Professional Group on Information Theory, 3(3), 68-89.
  • Palmer, L. (1974). Coarse frequency estimation using the discrete Fourier transform (Corresp.). IEEE Transactions on Information Theory, 20(1), 104-109.
  • Rife, D. C. B. P., & Boorstyn, R. (1974). Single tone parameter estimation from discrete-time observations. IEEE Transactions on information theory, 20(5), 591-598.
  • Quinn, B. G. (1994). Estimating frequency by interpolation using Fourier coefficients. IEEE transactions on Signal Processing, 42(5), 1264-1268.
  • Quinn, B. G. (1997). Estimation of frequency, amplitude, and phase from the DFT of a time series. IEEE transactions on Signal Processing, 45(3), 814-817.
  • Macleod, M. D. (1998). Fast nearly ML estimation of the parameters of real or complex single tones or resolved multiple tones. IEEE Transactions on Signal processing, 46(1), 141-148.
  • Jacobsen, E., & Kootsookos, P. (2007). Fast, accurate frequency estimators [DSP Tips & Tricks]. IEEE Signal Processing Magazine, 24(3), 123-125.
  • Candan, Ç. (2013). Analysis and further improvement of fine resolution frequency estimation method from three DFT samples. IEEE Signal Processing Letters, 20(9), 913-916.
  • Salor, Ö. (2009). Spectral correction-based method for interharmonics analysis of power signals with fundamental frequency deviation. Electric power systems research, 79(7), 1025-1031.
  • Kalair, A., Abas, N., Kalair, A. R., Saleem, Z., & Khan, N. (2017). Review of harmonic analysis, modeling and mitigation techniques. Renewable and Sustainable Energy Reviews, 78, 1152-1187.
  • Akdağ, O , Yeroğlu, C . (2018). 154 kV İletim Hatlarındaki Akım Transformatörlerinde Simülasyon Modeli ile Harmonik Bozulmaya Dayalı Doygunluk Algılama Yöntemi . Avrupa Bilim ve Teknoloji Dergisi , (14) , 353-363.
  • Fidan, P , Akdemir, H , Kekezoğlu, B , Adiyıl, İ . (2018). İstanbul’da Bir Raylı Sistem Tesisi’ne Ait Harmonik Analizi ve Çözüm Önerileri . Avrupa Bilim ve Teknoloji Dergisi , (14) , 215-221.
  • Gökozan, H . (2021). The Effect of an Induction Heating System on Power Quality Parameters . Avrupa Bilim ve Teknoloji Dergisi , (21) , 25-30.
  • Compatibility, E. General Guide on Harmonics and Interharmonics Measurements and Instrumentation. IEC Standard, 61000-4.
  • Lin, H. C. (2011). Power harmonics and interharmonics measurement using recursive group-harmonic power minimizing algorithm. IEEE Transactions on Industrial Electronics, 59(2), 1184-1193.
There are 16 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Kenan Gençol 0000-0003-4044-3482

Early Pub Date July 29, 2021
Publication Date November 30, 2021
Published in Issue Year 2021 Issue: 27

Cite

APA Gençol, K. (2021). Choosing The Optimum Frequency Estimator Under System Frequency Deviations In Power Systems. Avrupa Bilim Ve Teknoloji Dergisi(27), 670-675. https://doi.org/10.31590/ejosat.904157