Research on Harmonic Separation Algorithm for New Power Systems Based on Deep Networks
The new power systems contain a large number of power electronic devices,resulting in complex har-monic content,with harmonic frequencies varying over time.Monitoring the harmonic components can improve the power quality and efficiency of these systems.Empirical Mode Decomposition(EMD)can resolve the spectral information of power system signals,such as the amplitude and phase of each harmonic.This paper proposes an adaptive harmonic decomposition model based on deep neural networks,where the model parameters can be auto-matically selected without relying on manual settings,thus avoiding human-induced errors.Finally,test cases are presented to verify the effectiveness of the proposed method.
deep networkneural networknew power systemharmonic separation
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