A Rearch To Algorithm Of Data Compression Of Power Quality

Energy is a special product provided by power enterprises to users. Now, power quality has drawn extensive attention. With the increasing development of operation intelligence and remote monitoring in power system, it has become issues of concern how to obtain effective power quality data compression, to reduce its storage space and to reduce data transmission volume and time.Based on the analysis of PQZip technology, the advanced data compression technology in the field of power quality data compression, a new lossy compression algorithm combining the advantages of Fast Fourier Transform (FFT) and wavelet transform is proposed in this paper, and after lossy compression, a lossless LZW compression algorithm is used to do further compression, aiming to better compression effect. After the sampling of the noisy power quality signal, wavelet threshold denoising is done to the signal in order to effectively extract its characteristics. Then detect it using dyadic wavelet transform: If the detected signal is stationary, FFT is used to compress it to acquire the corresponding spectrum and to record different frequency components contained in original signal; otherwise, wavelet packet transform is used to do the compression. During the compression, all levels of decomposition coefficients of wavelet packet are thresholding processed to reserve singularity points which are related to original signal and to ignore the points which have nothing to do with the signal singularity. At last, lossless compression algorithm of LZW is used to do further compression to the lossy compression results so as to achieve a more efficient compression effect. In addition, in this paper it builds models of four kinds of conventional steady-state disturbance signals and the five kinds of common transient signals in Matlab simulation platform. And then these signals, as well as the actual voltage and current signals provided by Siemens AG, are de-noised, detected and compressed in strong noise environment. After the compression results comparion with the ones of PQzip and classic wavelet transform compression method, it demonstrates that the proposed approach gives a effective and better way for power quality data compression.