Research On Data Compression Methods And Its Application In Electric Power System

With the development of economy and society, high quality power has become thecommon needs of the power system and power consumers, which sets high requirementsfor more efficient power quality detection and analysis technology, to be based on theacquisition and compression of power data. In recent years, researchers have studied andtried various methods for power data compression. There would be certain data loss byusing traditional lossy compression methods when the power data volume is large, and thekey characteristics of signals are often lost; the lossless compression method can keep theoriginal information intact, but it requires higher hardware conditions and takes up moreresources.In this dissertation, an in-depth study is performed on the application of CompressiveSensing theory in power quality data compression and reconstruction and the traditionalpower quality lossless compression algorithm LZW is introduced as a comparison.Compressive Sensing does not rely on Nyquist-Shannon Sampling Theorem and thesampling rate based on the structure and characteristics of signals is far below traditionalsampling rate, for it makes signal acquisition and compression one step at the acquisitionside, which greatly reduces the data volume to be processed. In contrast with LZW, theCompressive Sensing performs better in terms of the two indicators of compression ratioand reconstruction error.First, the basic theory of data compression method and the current research anddevelopment tendency of Compressive Sensing theory are introduced respectively in thispaper. Moreover, by reference to the related standards of IEEE power quality and relevantliterature at home and abroad, the power quality disturbance signals are classified and amath model of power quality disturbance signals is also built.Second, the basic theories of LZW lossless compression algorithm and Compressivesensing method are elaborated in this paper, and on the basis of these two methods, theimplementation process of signal compression and reconstruction is introducedrespectively, and a summary is made on the advantages and disadvantages of the two methods in theory as well as the necessary conditions for the application of the twomethods.Finally, simulation experiment of the two methods is made based on themathematical model of power quality disturbance signals and the reconstructionperformance is analyzed. These two methods are compared and evaluated according tocompression effect and reconstruction error. This dissertation also demonstrates thewriter’s opinion on the development trend of Compressive sensing in the future.