Harmonic and Interharmonic Detection in Power Systems Based on Fractal-Optimized Variational Mode Decomposition

TL;DR

This paper presents a novel fractal-optimized variational mode decomposition method for accurately detecting harmonic and interharmonic signals in power systems, improving upon existing techniques like EMD and EEMD.

Contribution

It introduces a fractal box dimension-based parameter selection for VMD, enabling automatic determination of decomposition layers for power signal analysis.

Findings

More accurate harmonic detection than EMD and EEMD

Effective extraction of harmonic and interharmonic signals

Validated with simulation and real-world data

Abstract

The proposed method introduces a parameter determination approach based on the minimum Fractal box dimension (FBD) of Variational Mode Decomposition (VMD) components, aiming to address the issue of manual determination of VMD decomposition layers in advance. Initially, VMD is applied to the original power signal, and the layer number for VMD decomposition is determined by selecting the K value associated with the smallest fractal box dimension among its components. Subsequently, several Intrinsic Mode Functions (IMFs) are obtained as fundamental, harmonic, and interharmonic signals representing different aspects of the power system. Furthermore, Hilbert transform(HT) is employed to extract instantaneous amplitude and frequency information from these harmonic signals. Experimental evaluation using simulation data and real-world power system data demonstrates that compared to Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD), our proposed method achieves more accurate identification and effective extraction of harmonic signals.