A Measurement Method for Wide-frequency Harmonic Signal in Power Grid Based on Window Interpolation FFT and RLS-Adaline Neural Network

Abstract

With the increase of non-linear loads in power grid and the development of power electronics, the growing serious harmonic pollution has put forward higher requirements for the accuracy and real-time performance of the measurement method. For this problem, this paper proposes a wide-frequency harmonic signal measurement method based on window interpolation FFT and adaptive neural network. After the window function is selected, the frequency of harmonic is estimated by double-spectrum-line interpolation algorithm based on three-term third derivative Nuttall window, and then the smoothed frequencies are input into RLS-Adaline neural network to estimate the amplitude and phase of each harmonic. The simulation results show that the proposed method has higher measurement accuracy and stability under few data conditions and low signal-to-noise ratios than conventional window interpolation algorithms. High accuracy measurement of harmonics with short time window in the range of 0∼2.5kHz is effectively realized.