Pure harmonics extracting from time-varying power signal based on improved empirical mode decomposition

• We enhance the accuracy and integrality of harmonics sifted in power signal.
• We employ improved fast Fourier transform and components pre-sifting strategies.
• Cooperative chaotic particle swarm optimization (CCPSO) is presented here.
• The parameters for constructing masking signals are optimized by CCPSO.
• The proposed method can be used in signal analysis in different scenarios.

Harmonic decomposition makes a great impact on power system operation, especially devices with frequency converters are widely used in modern society. In this paper, a hybrid method based on improved empirical mode decomposition enhanced with masking signals is presented to extract single-frequency harmonics from disturbed power signals accurately. The parameters for building masking signals are optimized by cooperative chaotic particle swarm optimization, where the Logistic chaos and cooperative evolution are employed to improve the convergence accuracy and avoid trapping into local minima. For improving the performance further, the improved fast Fourier transform based on Nuttall window and harmonics pre-extracting procedure are introduced to enhance the decomposition accuracy and reduce the instantaneous magnitude error in extracting time-varying power signal. The synthetic and field experiments demonstrate that the proposed method reveals significant improvements in the integrality and decomposition accuracy of harmonics extracted from time-varying power signal.