The Research On Compression Method Of Power Quality Data Based On Wavelet Transform

With the development of smart gird, the application of electronic devices arebringing more and more new power quality problems. Real-time monitoring andanalysis on the gird has great significance for the study of power quality. Thereal-time and accurate data is also the premise for governance programs ofeffective implementation. Power quality data is always with high precision, andhuge number. The application of effective compression method can reduce thepressure of communication systems from the large amounts of data, and also cancontrol the cost for transmission and storage. The paper studied the compressionmethod of recorded data for wave features of power quality monitoring data. Thismethod can achieve a high compression ratio by using wavelet transform, whichhas a time-frequency analysis of characteristics and lossless compression method.This paper will use dq0transform to turn the three-phase power qualitysignal to d, q and0phases. This transform method mine the redundant databetween three-phase signals to improve compression ratio. It retains the powerquality features information without damaging information.Use wavelet transform threshold compression method to compress thepower quality data. Due to the sparsity of the wavelet coefficients, energyfocused on a limited wavelet coefficients. Therefore we can discard thecoefficient which is less than the selected threshold in each dimension to reducethe coefficients for wavelet reconstruction. It can get a effective datacompression through wavelet reconstruction of retained coefficients, andapproach the original signal in maximum extent.Proposed a multi-identify LZ77lossless algorithm for a further compressionof wavelet coefficients. On the basis of LZ77algorithm, proposed improvementin two aspects: extended the slide dictionary, and output code. And using Huffman coding method to remove redundant since the set the minimumnumber of matches. This method can effectively improve the compression ratiounder the premise that other indicators are not affected.This paper made simulation of typical power quality disturbance signalssuch as voltage sag, swell and harmonic and use compressed the signals. Evaluate theeffect of this compression method with compression ratio and root mean squareerror. And make a horizontal contrast with other compression methods. After alot of simulation results, the figures out that the compression ratio is higher thansimilar methods after wavelet threshold compression method with the method inthis paper. It achieved a better compression while the root mean square error issmaller.