Study On Data Compression Of Power Quality Based On Compressive Sensing Theory

With national economy developing continuously and the scale of powerincreasing rapidly, the electric department and users have become very concernedabout power quality problems. In order to improve and enhance the power quality,the power sector needs to monitor various real-time power signals for analyzingpower quality and taking control and compensation measures effectively.Therefore, for effective power quality analysis, they must take some steps first,such as acquisition, compression, storage, transmission, detection andidentification. Monitoring and storage power quality’s failure and interferencesignal has become their main everyday job.However, if power signal problems happen, it will contain a very wide rangeof spectral components. On the basis of Shannon sampling theorem, the samplingfrequency must be more than twice the maximum frequency of the original signal,so these sampling recorded data may be as high as the number of megabytes persecond level. Such high-precision sampling requirement will create a huge amountof data. And, it’s difficult to store and transmit such a huge amount of recordeddata. Therefore, to avoid losing important information and reduce the amount ofdata, it is necessary to carry out the power quality data compression.Current power quality data compression method starts with continuous powerdata acquisition at a very high sampling rate, and then abandons most of theredundant data by high-performance compression means, which will result inacquisition equipment large sampling pressure and cause great waste of storageresources. If the sampling and compression process can be integrated, it will be aneffective solution to solve the problem of massive power quality monitoring data,and ease the burden on data storage and transmission to a great extent.In2006, compressive sensing theory has brought a big breakthrough forsignal processing and analysis field. The theory is able to solve the drawbacks ofthe power data acquisition. It can combine data sampling and data compressiontogether. At first this paper studies the method of data compression using theconventional Fourier transform and wavelet transform, and then the compressivesensing theory is introduced to the power quality data compression. Compared towavelet transform, compressed sensing compression can obtain better compressionperformance. And it provide a new method of analysis and processing to powerdata acquisition and compression, and provide new ideas for power qualityanalysis, and will eventually be able to better solve power quality problems.