Interharmonic Parameter Identification Based on Adaptive FSST and DEO3S

Harmonics and interharmonics have a significant impact on the safe operation of power systems, and accurately identifying interharmonics in power systems is the basis of harmonic suppression. The accuracy with which interharmonic components in power systems are detected is easily affected by mode aliasing and noise; to address this issue, a method of detecting them based on an adjusted Fourier-based synchrosqueezing transform (AFSST) and the three-point symmetric difference energy operator (DEO3S) is proposed. First, in order to reduce the influence of endpoint effects on detection accuracy, an improved waveform feature-matching extension method is utilized to reduce endpoint effects generated during the FSST decomposition process. Then, because it is difficult to adaptively determine the number of ridges in the FSST decomposition process, the energy difference and normalized cross-correlation coefficient are utilized as the criterion for determining the number of modal decompositions in the FSST, thereby improving the accuracy of the ridge number. Finally, using AFSST, the harmonic/interharmonic signals are decomposed into a set of intrinsic mode functions (IMFs). The instantaneous frequency and amplitude of each component are extracted using DEO3S, enabling the accurate detection of harmonics and interharmonics in the power system. Experimental analysis was conducted using simulation data, arc furnace experimental system data, and hardware experimental platform data. The results showed that the proposed method can accurately detect harmonic/interharmonic parameters under different levels of noise interference. Compared with the FSST, EMD, EEMD, and CEEMDAN methods, the amplitude detection accuracy of the proposed method is improved by 0.21%, 0.78%, 0.64%, and 0.75%, respectively, and the amplitude detection accuracy is improved by 1.39%, 3.31%, 2.04%, and 3.14%, respectively.