A rule-based expert system for harmonic load recognition

This paper presents a new method for identifying the different types of single phase nonlinear loads as sources of harmonic disturbances in a power system. The method combines the use of signal processing and artificial intelligence techniques. Fast Fourier transform and fractal analyses have been used to extract features of the harmonic signatures of the various nonlinear loads from the sampled input current waveforms. Intelligent and automatic harmonic load recognition process is achieved by using a rule-based expert system. The expert system has been verified using real measurements and the results show that the system give accurate identification of the single phase nonlinear loads such as personal computer, fluorescent lights, uninterruptible power supply and oscilloscope.

[1]  Irene Yu-Hua Gu,et al.  Expert system for voltage dip classification and analysis , 2001, 2001 Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.01CH37262).

[2]  D. D. Shipp,et al.  Expert system for analysis of electric power system harmonics , 1995 .

[3]  P. Verde,et al.  Estimating the net harmonic currents produced by selected distributed single-phase loads: computers, televisions, and incandescent light dimmers , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[4]  Edward J. Powers,et al.  A scalable PQ event identification system , 2000 .

[5]  M. M. Morcos,et al.  An adaptive neuro-fuzzy intelligent tool and expert system for power quality analysis. I. An introduction , 1999, 1999 IEEE Power Engineering Society Summer Meeting. Conference Proceedings (Cat. No.99CH36364).

[6]  Yoshikazu Fukuyama,et al.  Development of an Expert System for Analyzing Faults in Power Systems Using Artificial Neural Network Based Waveform Recognition , 1991 .

[7]  W. Vilcheck,et al.  Expert system for analysis of electric power system harmonics , 1993, Conference Record of 1993 Annual Pulp and Paper Industry Technical Conference.

[8]  Azah Mohamed,et al.  Characterizing nonlinear load harmonics using fractal analysis , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[9]  E. Styvaktakis,et al.  Expert System for Classification and Analysis of Power System Events , 2002, IEEE Power Engineering Review.

[10]  Y. Ueki,et al.  Development of an expert system for analyzing faults in power system using artificial neural network based waveform recognition , 1991, 1991., IEEE International Sympoisum on Circuits and Systems.

[11]  J. Schlabbach.  Expert system measures harmonics and EMC , 1994, IEEE Computer Applications in Power.

[12]  W.E. Kazibwe,et al.  Expert system targets power quality issues , 1992, IEEE Computer Applications in Power.

[13]  Min Wang,et al.  Real-time power quality waveform recognition with a programmable digital signal processor , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[14]  Pradipta Kishore Dash,et al.  Classification of power system disturbances using a fuzzy expert system and a Fourier linear combiner , 2000 .