Electric Harmonic Liability Quantification Method and Resonance Suppression Method Based on Data Fusion

In the context of high power electrification rate in urban power grids, the power system exhibits the characteristics of multiple nonlinear user interactions, which exacerbates harmonic pollution. In addition, the background harmonic fluctuations will be more drastic and the harmonic emission characteristics between different harmonic sources will be correlated, thus bringing new challenges to the quantification of harmonic liability. Introducing the idea of data fusion based on Kalman filtering, and integrating the advantages of the fluctuation volume method and the independent component method, a system-side harmonic impedance calculation method based on the data fusion method is proposed, which can still maintain high calculation accuracy when the background harmonic fluctuation is violent and the system-side and user-side harmonic sources are correlated to a certain extent. The method still has high calculation accuracy when the background harmonic fluctuation is intense and each harmonic source is no longer independent. Simulation analysis and actual engineering cases verify the feasibility of the proposed method. For the user-side harmonic sources, according to their harmonic emission characteristics, the harmonic pollution can be limited to a certain range by adding single-tuned filters for the harmonics with higher number of contents.