Automatic extraction algorithm of small signal in power system considering the fluctuation of eigenvalue

Abstract

The conventional automatic extraction algorithm of small interference signals in the power system mainly uses the selfprobability density function to obtain the signal peak position, which is vulnerable to the influence of signal convergence conditions, leading to the inaccurate step of the extracted small interference signals. In this context, it is necessary to consider the fluctuation of characteristic importance values and design a new automatic extraction algorithm for small interference signals in the power system. In this research, by combining the influence of time delay, the automatic extraction model of small interference signals in the power system is established, the automatic extraction load of small interference signals is predicted considering the important value of characteristics, and the automatic extraction eigenvalue of small interference signals in the power system is analyzed, thus realizing the automatic extraction of small interference signals in power system. The experimental results show that the designed automatic extraction algorithm for small interference signals in a power system considering the fluctuation of characteristic importance values extracts more accurate small interference signal steps, which proves that the designed automatic extraction algorithm for small interference signals in the power system has good performance, reliability and certain application value, and can make certain contributions to improving the operation stability of the power system.