Harmonic Load Identification Using Complex Independent Component Analysis

Due to an increase of power-electronic equipment installation and other harmonic sources, the identification and estimation of harmonic loads are of concern in electric power transmission and distribution systems. Conventional harmonic state estimation requires a redundant number of expensive harmonic measurements. In this paper, we explore the use of a statistical signal-processing technique, known as independent component analysis (ICA) for harmonic source identification and estimation. If the harmonic currents are statistically independent, ICA is able to estimate the currents using a limited number of harmonic voltage measurements and without any knowledge of the system admittances or topology. The results are presented with computer simulations for the modified IEEE 30-bus test system.

[1]  Paulo F. Ribeiro,et al.  Impact of Aggregate Linear Load Modeling on Harmonic Analysis: A Comparison of Common Practice and Analytical Models , 2003, IEEE Power Engineering Review.

[2]  G. T. Heydt,et al.  Dynamic state estimation of power system harmonics using Kalman filter methodology , 1991 .

[3]  Kit Po Wong,et al.  Harmonic state estimation: a method for remote harmonic assessment in a deregulated utility network , 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382).

[4]  E. Oja,et al.  Independent Component Analysis , 2013 .

[5]  Neville R. Watson,et al.  Identification of harmonic sources of power systems using state estimation , 1999 .

[6]  Y. Liu,et al.  Test systems for harmonics modeling and simulation , 1999 .

[7]  G. T. Heydt,et al.  Identification of harmonic sources by a state estimation technique , 1989 .

[8]  Kit Po Wong,et al.  A method of utilising non-source measurements for harmonic state estimation , 2000 .

[9]  W. Xu,et al.  Harmonic impedance measurement using three-phase transients , 1998 .

[10]  R.K. Hartana,et al.  Constrained neural network based identification of harmonic sources , 1990, Conference Record of the 1990 IEEE Industry Applications Society Annual Meeting.

[11]  Erkki Oja,et al.  Independent component analysis: algorithms and applications , 2000, Neural Networks.

[12]  D. Niebur,et al.  Impact of Sample Size on ICA-Based Harmonic Source Estimation , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[13]  G. Montanari,et al.  Stochastic evaluation of harmonics at network buses , 1995 .

[14]  Aapo Hyvärinen,et al.  A Fast Fixed-Point Algorithm for Independent Component Analysis of Complex Valued Signals , 2000, Int. J. Neural Syst..

[15]  Dagmar Niebur,et al.  Load profile estimation in electric transmission networks using independent component analysis , 2003 .

[16]  Mark Sumner,et al.  A technique for power supply harmonic impedance estimation using a controlled voltage disturbance , 2002 .

[17]  A. Testa,et al.  Time-Varying Harmonics: Part II-Harmonic Summation and Propagation , 2001, IEEE Power Engineering Review.

[18]  Erkki Oja,et al.  An Experimental Comparison of Neural Algorithms for Independent Component Analysis and Blind Separation , 1999, Int. J. Neural Syst..

[19]  N. R. Watson,et al.  Marginal Pricing of Harmonic Injections , 2002, IEEE Power Engineering Review.

[20]  Paulo F. Ribeiro,et al.  Time-varying harmonics. II. Harmonic summation and propagation , 2002 .

[21]  Paulo F. Ribeiro,et al.  Time-varying harmonics. I. Characterizing measured data , 1998 .

[22]  Fan Zhang,et al.  Power system harmonic state estimation , 1994 .

[23]  Neville R. Watson,et al.  Continuous harmonic state estimation of power systems , 1996 .

[24]  Jean-Francois Cardoso,et al.  Blind signal separation: statistical principles , 1998, Proc. IEEE.

[25]  A. J. Bell,et al.  A Unifying Information-Theoretic Framework for Independent Component Analysis , 2000 .

[26]  Aapo Hyvärinen,et al.  Fast and robust fixed-point algorithms for independent component analysis , 1999, IEEE Trans. Neural Networks.