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Power Quality Data Compression Based on Iterative PCA Algorithm in Smart Distribution Systems

机译:智能PC系统中基于迭代PCA算法的电能质量数据压缩。

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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.
机译:为了减轻智能配电系统中电能质量(PQ)数据传输和存储的压力并帮助进行PQ分析,引入了基于迭代PCA(主成分分析)算法的多通道数据压缩。所提出的方法使用PCA来减少数据的冗余,以达到压缩数据的目的。为了提高计算速度,提出了一种迭代方法来计算协方差矩阵的主分量。通过现场PQ数据测试验证了该方法的正确性和可行性。与离散小波变换(DWT)方法相比,该方法在压缩率和重建精度上具有良好的性能。

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