This paper introduces a new method for the simultaneous measurement of harmonic and supraharmonic distortion with improved robustness against amplitude and power frequency deviations. The proposed algorithm is based on wavelet analysis and it is designed to analyze a 10 cycles measurement interval, something crucial when implementing methods to measure harmonic and supraharmonic content according to the IEC 61000-4-7 standard. Discrete Fourier Transform (DFT)-based methods, instead, must analyze a fixed 200 ms interval in order to avoid apparent shifts of the supraharmonic frequency components. The results of the experimental measurements presented in the paper show that the DFT-based methodology suggested in the IEC 61000-4-7 standard produces results affected by the value of the power frequency and amplitude while the proposed method, instead, is insensitive to them. This feature also removes the need of a previous high pass filtering stage, required for the IEC method. Moreover, the proposed method has the additional advantage of working on the same measurement interval to calculate both harmonics and supraharmonics, which reduces the complexity of data handling by avoiding multithreaded Data Acquisition (DAQ) operations.

Abstract-The proliferation of non-linear loads in both industrial and residential distribution grids leads to undesirable non-sinusoidal and fluctuating harmonic pollution on voltage and current waveforms. New analysis tools, such as wavelets, are being used to overcome the problems posed by the use of the Fourier Transform when analyzing complex waveforms. Nevertheless, the selection of the wavelet basis must be done carefully to minimize spectral leakage due to the non-exact frequency discrimination. In this context, this paper proposes an objective method for comparing different wavelet families for the measurement of harmonic contents. This methodology is applicable for determining the best filter among the 53 preselected structures according to the following requirements: frequency selectivity, computational complexity, convolution results and observed spectral leakage. With all these considerations, the Butterworth IIR filter of order 29 was found to be the best wavelet decomposition structure to achieve an effective harmonic analysis up to the 50 th order.

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