Fundamental Frequency Tracking Of Power Signal Based On The Adaptive Strong Tracking Filter

The frequency of power grid reflects the dynamic balance between power consumption and load, which is an important reference for the normal operation of the control system. On power system frequency dynamic tracking estimation is to study the power system control, safety assessment and analysis of power quality based, and its importance is self-evident, so the study of tracking the dynamic changes of the grid frequency is a very practical significance, on the electric power industry will have a positive impact. After analyzing the frequency characteristic of the power grid, the scholars put forward a variety of power grid frequency tracking method, and proposed the method of Fourier transform in the deterministic harmonic signal. Under the condition of non stationary distorted signal, the researchers put forward a differential orthognal transformation method based on digital filter for frequency tracking. But so far, traditional frequency tracking technology of system state mutation or in the presence of strong interference of poor processing performance, under the condition of signal distortion how to deal with the fundamental signal do real-time and accurate tracking becomes a problem to be solved.In this paper, combined with the actual power system model, the ideal voltage signal is a standard sine signal, considering the power system at the moment of external disturbances, not only the voltage change and fundamental frequency will fluctuate. In order to reduce the harmonic and noise effect on the fundamental frequency tracking accuracy, this paper through study and analysis of different methods, the wavelet transform is applied to extract the fundamental signal under the condition of signal distortion, Firstly, the power signal was preprocessed to extract the fundamental wave by wavelet filtering. signal filter in addition to the fundamental frequency of the higher harmonics, inter harmonics and random noise components. Through the simulation, the original voltagesignal is separated by the wavelet transform, and the fundamental component can be separated accurately. In order to ensure that the fundamental wave model is not interfered, the stability is enhanced. In this paper, a model reference adaptive control method is used, which can be used to adjust adaptive Lyapunov-MRAC algorithm to reduce the influence of external disturbance or internal noise. Based on the combination of the fundamental model and extended Kalman filter, the adaptive filtering principle is introduced into the grid to study fundamental frequency tracking. the establishment of the state equation and measurement equation, the fundamental frequency for real-time tracking processing, In frequency tracking in the process of simulation were enumerated and analyzed the advantages and disadvantages of this algorithm and the need to address the problem proposed improved algorithm. The simulation results show that the ASTF algorithm can achieve real-time accurate tracking of fundamental frequency. On the one hand, adaptive real-time control of the measurement noise of R, on the other hand, the concept of bad data in measurement of adaptive elimination.