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Power Quality Data Compression Based on Iterative PCA Algorithm in Smart Distribution Systems
School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan, China
School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan, China
College of Computer Science, South Central University for Nationalities, Wuhan, China
- 1 School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan, China
- 2 School of Electronic and Electrical Engineering, Wuhan Textile University, Wuhan, China
- 3 College of Computer Science, South Central University for Nationalities, Wuhan, China
Smart Grid and Renewable Energy·Volume 08 (2017)·Pages 366–378·Published 21 December 2017·DOI10.4236/sgre.2017.812024
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Abstract
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.
KeywordsSmart Distribution SystemsPower QualityData CompressionPrincipal Component Analysis (PCA)
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