Parameter Identification of Generator Excitation System Based on Improved Grey Wolf Optimization
Hengming Liu, Lu Cao · Journal of Physics Conference Series · 2020
Abstract In order to ensure the accuracy of power system modelling and the reliability of safety and stability analysis, it is important to confirm the true parameters of the excitation system. This paper proposes that using hunting group division strategy and convergence factor non-linear decreasing strategy to improve the standard grey wolf optimization algorithm, and applied it to the identification of the generator excitation system. The simulation results show that the identification of the excitation system based on the improved grey wolf optimization algorithm has higher identification accuracy and stability, which provides an effective new method for the parameter identification of the nonlinear.