A Parameterization Power Data Compress Using Strong Trace Filter and Dynamics

Abstract

This paper proposed a parameterization power data compress using strong trace filter (STF) and dynamics (Dyn). The STF estimates the fundamental and harmonic component parameters. When there are only fundamental and harmonic components, the power data frame is compressed in parameter form. When there are other disturbances, the fading factors of STF and Dyn are used to recognize possible transient disturbances and interharmonics, respectively. By subtracting the fundamental and harmonic components, the residue of disturbances is coded by lifting wavelet transform (LWT). Then, the estimated parameters and LWT coefficients are used to reconstruct the power signal. The proposed method places emphasis on two important steps of parameterization power data compress and has a better performance than that of the related methods when the compress ratio is the same.