Intelligent system for identification of harmonics originating from single phase nonlinear loads

This paper presents a new method for identifying harmonic sources originating from various single phase nonlinear loads such as the uninterruptible power supply, personal computer, fluorescent lamp with electronic ballast and personal computer. Signal processing techniques based on fractal and fast Fourier transform analyses have been used to characterize the harmonic signatures of the different types of nonlinear loads. The features obtained from the analyses characterize the harmonic signature of a load type. The features extracted are in the form of fractal numbers, individual harmonic components, total harmonic distortion, crest factor and form factor. Identification of the harmonic sources is achieved by using a rule-based expert system in which the system recognizes and classifies the different types of nonlinear loads from the input current waveforms. The expert system with its user interface has been developed in MATLAB and it has been verified with real current measurements. The results obtained prove that the expert system gives accurate recognition of nonlinear loads. Such an intelligent system is useful for diagnosing a power quality related problem such as harmonics in which it can identify the harmonic source originating from single phase nonlinear loads.

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