基于压缩感知的含扰动电能质量信号压缩重构方法

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Abstract A method based on compressed sensing theory is proposed to realize the compressive sampling and nonlinear recovery. The compressibility and the sparsity of the disturbed power quality signals are analyzed, and the existing iterative greedy pursuit recovery algorithms are reviewed. Combined with the advantages of two typical algorithms SP and SAMP, an improved method named BSMP is proposed. Then the reconstruction performance of several typical greedy pursuit recovery algorithms are simulated and analyzed, using the power quality signals with steady or transient disturbances such as harmonics, interharmonics, voltage swell and sag, etc. Results verify the feasibility of the BSMP in recovering the power quality signals with mixed or single disturbances. Compared with the existing greedy algorithms, BSMP algorithm does not require sparsity level as prior information, and can realize the successful reconstruction absolutely with faster speed and higher compression ratio.

Key words： Compressed sensing matching pursuit reconstruction algorithm sparse representation power quality

Received: 28 April 2014 Published: 28 April 2016

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	Chen Lei
	Zheng Dezhong
	Liao Wenzhe

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Chen Lei,Zheng Dezhong,Liao Wenzhe. Method Based on Compressed Sensing for Compression and Reconstruction of Power Quality Signals with Disturbances[J]. Transactions of China Electrotechnical Society, 2016, 31(8): 163-171.

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https://dgjsxb.ces-transaction.com/EN/ OR https://dgjsxb.ces-transaction.com/EN/Y2016/V31/I8/163

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