Parameter Identification of Doubly Fed Induction Generator (DFIG) using Particle Swarm Optimization (PSO) algorithm

The objective of this study is to determine the parameters of the doubly fed induction generator (DFIG), which is a crucial first step in wind turbine power generation. This research focuses on understanding the dynamics of the DFIG system and aims to develop more precise control systems for network movement and the exchange of active and reactive energy, especially at high speeds in this domain. This research utilizes the particle swarm optimization (PSO) approach to perform DFIG parametric identification. The model simulation is adapted to the identical settings in the MATLAB/Simulink software environment. The identification findings of the "PSO" method are compared to those of traditional testing and validated based on their accuracy and convergence to the energy source values obtained by the dSPACE panel. The findings obtained using the "PSO" algorithm demonstrate superior effectiveness and performance compared to the conventional identification approach.