Harmonic Measurement Method and System Design Based on Self-Compensating FFT

Harmonics in power systems not only affect the operational efficiency of equipment but also have the potential to cause system failures and stability issues. Therefore, accurate measurements and analyses of harmonics are of great significance. The conventional fast Fourier transform (FFT) is widely used for harmonic analysis; however, its performance can be affected by issues such as spectral leakage and the fence effect. These issues can result in significant errors in frequency and amplitude estimation, often failing to meet the requirements for high-precision signal processing. To address this challenge, this study proposes a harmonic analysis method based on the self-compensating FFT. After signal preprocessing steps such as windowing and zero-padding, the self-compensating FFT integrates frequency and amplitude correction into a unified framework. It first estimates the frequency deviation using a three-point interpolation method based on the energy distribution of adjacent spectral peaks, and then constructs a data-driven amplitude correction model based on the updated frequency - amplitude relationship. This method improves harmonic analysis accuracy by optimizing frequency and amplitude corrections in tandem, effectively eliminating frequency offset and amplitude errors inherent in the conventional FFT. Experimental results demonstrate that compared to conventional FFT, the self-compensating FFT reduces errors in frequency and amplitude estimation by 99.6%-99.8% and 95%-98%, respectively. These findings demonstrate the significant optimization performance of the proposed method.