Author(s)

Ming Zhang^1*, Yiming Zhan¹, Shunfan He²

¹School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan, China.
²College of Computer Science, South Central University for Nationalities, Wuhan, China.

To reduce the stress of data transmission and storage for power quality (PQ) in smart distribution systems and help PQ analysis, a multichannel data compression based on iterative PCA (principal component analysis) algorithm is introduced. The proposed method uses PCA to reduce the redundancy of data to achieve the purpose of compressing data. In order to improve the calculating speed, an iterative method is proposed to compute the principal components of the covariance matrix. The correctness and feasibility of the proposed method are verified by field PQ data tests. Compared with discrete wavelet transform (DWT) method, the proposed method has good performance on compression ratio and reconstruction accuracy.

Smart Distribution Systems, Power Quality, Data Compression, Principal Component Analysis (PCA)

Zhang, M. , Zhan, Y. and He, S. (2017) Power Quality Data Compression Based on Iterative PCA Algorithm in Smart Distribution Systems. Smart Grid and Renewable Energy, 8, 366-378. doi: 10.4236/sgre.2017.812024.