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Tytuł artykułu

Power grid impedance tracking with uncertainty estimation using two stage weighted least squares

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents a new method for simultaneous tracking of varying grid impedance and its uncertainty bounds. Impedance tracking consists of two stages. In the first stage, the actual noise estimate is obtained from least squares (LS) residua. In the second stage, the noise covariance matrix is approximated with the use of residual information. Then weighted least squares (WLS) method is applied in order to estimate impedance and background voltage. Finally uncertainty bounds for impedance estimation are computed. The robustness of the method has been verified using simulated signals. The proposed method has been compared to sliding LS. The results have shown, that the method performs much better than the LS for all considered cases, even in the presence of significant background voltage variations.
Rocznik
Strony
99--110
Opis fizyczny
Bibliogr. 30 poz., rys., tab., wykr., wzory
Twórcy
autor
  • AGH University of Science and Technology, Department of Measurement and Electronics, al. A. Mickiewicza 30, 30-059 Kraków, Poland
  • AGH University of Science and Technology, Department of Measurement and Electronics, al. A. Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • [1] Kechroud, A., Myrzik, J. M. A., & Kling, W. L. (2009, July). A power system equivalent impedance based voltage control. In Power & Energy Society General Meeting, 2009. PES'09. IEEE (1-5). IEEE.
  • [2] Otomański, P., & Wiczyński, G. (2010, June). Search for disturbing loads in power network with the use of voltage and current fluctuation. In Nonsinusoidal Currents and Compensation (ISNCC), 2010 International School on (197-200). IEEE.
  • [3] Robert, A., et al. (1997, June). Guide for assessing the network harmonic impedance. In Electricity Distribution. Part 1: Contributions. CIRED. 14th International Conference and Exhibition on (IEE Conf. Publ. No. 438) (Vol. 1, 3-1). IET.
  • [4] Xu, W., Ahmed, E. E., Zhang, X., & Liu, X. (2002). Measurement of network harmonic impedances: practical implementation issues and their solutions. Power Delivery, IEEE Transactions on, 17(1), 210-216.
  • [5] Borkowski, D., Wetula, A., & Bien, A. (2012, July). New method for noninvasive measurement of utility harmonic impedance. In Power and Energy Society General Meeting, 2012 IEEE (1-8). IEEE.
  • [6] Cespedes, M., & Sun, J. (2012, September). Online grid impedance identification for adaptive control of grid-connected inverters. In Energy Conversion Congress and Exposition (ECCE), 2012 IEEE (914-921). IEEE.
  • [7] Staroszczyk, Z. T. (2010, September). Combined, experimental data supported simulations in development of power grid impedance identification methods. In Harmonics and Quality of Power (ICHQP), 2010 14th International Conference on (1-7). IEEE.
  • [8] Gu, H., Guo, X., Wang, D., & Wu, W. (2012, May). Real-time grid impedance estimation technique for grid-connected power converters. In Industrial Electronics (ISIE), 2012 IEEE International Symposium on (1621-1626). IEEE.
  • [9] Hoffmann, N., & Fuchs, F. W. (2012, September). Online grid impedance estimation for the control of grid connected converters in inductive-resistive distributed power-networks using extended kalman-filter. In Energy Conversion Congress and Exposition (ECCE), 2012 IEEE (922-929). IEEE.
  • [10] Arrilaga, J., & Watson, N. R. (2003). Power system harmonics. Chichester: John Wiley & Sons.
  • [11] Cobreces, S., Rodriguez, P., Pizarro, D., Rodriguez, F. J., & Bueno, E. J. (2007, June). Complex-space recursive least squares power system identification. In Power Electronics Specialists Conference, 2007. PESC 2007. IEEE (2478-2484). IEEE.
  • [12] Langella, R., & Testa, A. (2006, June). A new method for statistical assessment of the system harmonic impedance and of the background voltage distortion. In Probabilistic Methods Applied to Power Systems, 2006. PMAPS 2006. International Conference on (1-7). IEEE.
  • [13] Hui, J., Yang, H., Lin, S., & Ye, M. (2010). Assessing utility harmonic impedance based on the covariance characteristic of random vectors. Power Delivery, IEEE Transactions on, 25(3), 1778-1786.
  • [14] Kay, S. M. (1993). Fundamentals of Statistical Signal Processing: Estimation Theory. Englewood Clifs: Prentice Hall.
  • [15] Oppenheim, A. V., Schafer, R. W., & Buck, J. R. (1999). Discrete-time signal processing (Vol. 5). Upper Saddle River: Prentice Hall.
  • [16] Tarasiuk, T. (2009). Comparative study of various methods of DFT calculation in the wake of IEC Standard 61000-4-7. Instrumentation and Measurement, IEEE Transactions on, 58(10), 3666-3677.
  • [17] Duda, K. (2010). Accurate, Guaranteed Stable, Sliding Discrete Fourier Transform [DSP Tips & Tricks]. Signal Processing Magazine, IEEE, 27(6), 124-127.
  • [18] Ferrero, A., & Ottoboni, R. (1992). A low-cost frequency multiplier for synchronous sampling of periodic signals. Instrumentation and Measurement, IEEE Transactions on, 41(2), 203-207.
  • [19] Cataliotti, A., Cosentino, V., & Nuccio, S. (2007). A phase-locked loop for the synchronization of power quality instruments in the presence of stationary and transient disturbances. Instrumentation and Measurement, IEEE Transactions on, 56(6), 2232-2239.
  • [20] Zhao, Q., Hsu, Y., Guo, B., Zhao, J. (2005, June). A digital filter design for digital resampling in power system applications. In Power and Energy Society General Meeting, 2005 IEEE (Vol. 2, 1849-1854). IEEE.
  • [21] Ghadam, A. S. H., Babic, D., Lehtinen, V., & Renfors, M. (2004, May). Implementation of Farrow structure based interpolators with subfilters of odd length. In Circuits and Systems, 2004. ISCAS'04. Proceedings of the 2004 International Symposium on (Vol. 3, III-581). IEEE.
  • [22] Borkowski, D., & Bien, A. (2009). Improvement of accuracy of power system spectral analysis by coherent resampling. Power Delivery, IEEE Transactions on, 24(3), 1004-1013.
  • [23] Duda, K. (2011). DFT interpolation algorithm for Kaiser-Bessel and Dolph-Chebyshev windows. Instrumentation and Measurement, IEEE Transactions on, 60(3), 784-790.
  • [24] Liu, S. (1998, October). An adaptive Kalman filter for dynamic estimation of harmonic signals. In Harmonics and Quality of Power Proceedings, 1998. Proceedings. 8th International Conference On (Vol. 2, 636-640). IEEE.
  • [25] Dash, P. K., Pradhan, A. K., & Panda, G. (1999). Frequency estimation of distorted power system signals using extended complex Kalman filter. Power Delivery, IEEE Transactions on, 14(3), 761-766.
  • [26] Karimi-Ghartemani, M., & Iravani, M. R. (2005). Measurement of harmonics/inter-harmonics of time-varying frequencies. Power Delivery, IEEE Transactions on, 20(1), 23-31.
  • [27] Pintelon, R., & Schoukens, J. (2004). System identification: a frequency domain approach. John Wiley & Sons.
  • [28] Wu, W. B., & Xiao, H. (2012). Covariance Matrix Estimation in Time Series. Handbook of Statistics, Vol. 30: Time Series Analysis: Methods and Applications, 187-209.
  • [29] Joint Committee for Guides in Metrology (2008). JCGM 100: Evaluation of measurement data - guide to the expression of uncertainty in measurement, JCGM, Tech. Rep., 2008.
  • [30] Borkowski, D. (2013, September). Power system impedance tracking using sliding, finite memory complex recursive least squares. In Proceedings of 17th IEEE Conference Signal Processing: Algorithms, Architectures, Arrangements, and Applications. IEEE.
Uwagi
EN
This research was founded by Polish National Science Centre under decision DEC-2012/05/B/ST7/01218.s
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-71dd8a2a-6234-4042-a110-e219e9ebf545
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