Estimation of Load Impedance in Presence of Harmonics
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Estimation of Load Impedance in Presence of Harmonics

Authors: Khaled M. EL-Naggar

Abstract:

This paper presents a fast and efficient on-line technique for estimating impedance of unbalanced loads in power systems. The proposed technique is an application of a discrete timedynamic filter based on stochastic estimation theory which is suitable for estimating parameters in noisy environment. The algorithm uses sets of digital samples of the distorted voltage and current waveforms of the non-linear load to estimate the harmonic contents of these two signal. The non-linear load impedance is then calculated from these contents. The method is tested using practical data. Results are reported and compared with those obtained using the conventional least error squares technique. In addition to the very accurate results obtained, the method can detect and reject bad measurements. This can be considered as a very important advantage over the conventional static estimation methods such as the least error square method.

Keywords: Estimation, identification, Harmonics, Dynamic Filter.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1328009

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References:


[1] D. H. Mollan, Harmonic impedance measurement using three phase transients, IEEE Trans. Power Delivery, Vol. 13, No.1, 1998, pp.272- 277.
[2] Wilsun Xu, Emad E. Ahmed, Xiqin Zhang and Xian Liu, Measurement of Network Harmonic Impedances: Practical Implementation Issues and Their solutions. IEEE Trans. on PWRD, Vol. 17, No. 1, Jan. 2002, pp. 210-216.
[3] A. Robert and T. Deflander, Guide for assessing the network harmonic impedances, CIGRE 36.05, Working Group CC02 Rep. March. 1993.
[4] H. Mori et-al., Identification of harmonic loads in Power Systems Using an Artificial Neural Network, Proc. 2nd Symp. Expert systems Applications to Power Systems, Seattle, WA., USA, 1989, pp.371-377.
[5] P.Ju, E. Handschin and D. Karlsson, Nonlinear Dynamic Load Modelling: Model and Parameter Estimation., IEEE Trans. On Power Systems, Vol. 11, No.4, Nov. 1996, pp. 1689-1695.
[6] Shun-Li Lu, Chin E. Lin and Ching Lien Huang, Suggested Power Definition and Measurement due to Harmonic Load, Electrical Power Systems Research Journal, Vol.53, 2000, pp.73-81.
[7] G.T. Heydt, Identification of Harmonic Sources by State Estimation Technique, IEEE Trans. On PWRD, Vol. 4, No.1, 1989, pp.569-575.
[8] S.A. Soliman N.H. Abbasy and M.E. El-Hawary, Frequency Domain modelling and Identification of nonlinear loads using a Least Error Squares Algorithm, Electric Power System Research Journal, Vol. 40, 1997, pp.1-6.
[9] G.S. Christensen and S.A. Soliman, Optimal Filtering of Linear Discrete Dynamic Systems Based on Least Absolute Value Approximations, Automatica, Vol. 26, No. 2, 1990.
[10] K.M.EL-Naggar, "A Fast Method for Identification of Symmetrical Components for Power System Protection", Electrical Power & Energy Systems, Vol.23, 2001, 813-817.
[11] Ahmaed M. AL-Kandari and Khaled M.EL-Naggar, Time Domain Identification of Nonlinear loads using Discrete Time-Filtering Estimator, Transmission & Distribution Conference and exhibition, IEEE/PES, Dallas, Texas, Sept. 2003, pp.126-131.
[12] E.B. Makram and S. Varadan, A Generalized Load Modelling Technique Using Actual Recorded data and its use in Harmonic Load Flow Program, Electric Power System Research Journal,Vol.27, 1993, pp.203-20.
[13] S.A. Soliman and M.EL-Hawary, Application of Kalman Filtering for on-Line Estimation of Symmetrical Components for Power System protection, Electric Power Systems Research J., Vol.38, 1997, pp.113- 123.