基于改进灰狼算法的发电机励磁系统参数辨识算法

Parameter Identification Algorithm for the Generator Excitation System Based on Improved Gray Wolf Optimization

为了确保电力系统建模的精确性和稳定分析的可靠性,确认励磁系统的参数至关重要。提出改进灰狼算法,应用发电机励磁系统的参数辨识,在MATLAB环境下进行仿真。结果表明:基于改进灰狼算法的励磁系统参数辨识方法具有更高的辨识精度与稳定性,对发电机励磁系统精确建模以及研究电力系统稳定性具有重要意义。

In order to ensure the accuracy and reliability of stability analysis of the modeling in the electric power system,it is of utmost importance to confirm the parameters of the excitation system.It was proposed to apply improved gray wolf optimization to parameter identification of the generator excitation system,and simulation was completed in the MATLAB background.The results showed that the parameter identification method for the excitation system based on improved gray wolf optimization had higher identification accuracy and stability and could be of great significance for accurate modeling of the generator excitation system and for the research on power system stability.