Parameter Identification of Doubly-Fed Induction Wind Turbine Based on the ISIAGWO Algorithm

Variations in generator parameters that occur during the operation of a doubly-fed induction wind turbine (DFIG) constitute significant factor degradation control performance. To address problem difficulty identifying multiple simultaneously DFIG, parameter identification method depending on adaptive grey wolf algorithm with an information-sharing search strategy (ISIAGWO) is proposed to solve low accuracy and slow speed DFIG. The easily obtainable outlet current was selected as observed quantity, trajectory sensitivity analysis performed five electrical DFIG derive its discriminability. Finally, recognition carried out using ISIAGWO MATLAB/Simulink simulation software, applying calculation functions. experimental results show has better accuracy, stability, convergence for DFIG’s identification.