Abstract: The transmission chain parameters of the doubly-fed wind turbine have an important impact on its stability. Since existing parameter identification algorithms are easy to fall into local optimum,an improved method based on particle swarm optimization（PSO）algorithm is proposed. First,in order to solve local optimum problem,an identification algorithm is proposed by improving the weight coefficient,acceleration coefficient and introducing concepts of crossover and mutation. Its effectiveness is verified by classical test function. Then,the simulation model of the doubly-fed wind turbine is established,based on which an effective measurement of parameter identification of transmission chain is proposed by exerting three-phase short-circuit fault excitation and trajectory sensitivity analysis. Finally,combined with the improved PSO algorithm and effective measurement,transmission chain parameter identification of the doubly-fed wind turbine is achieved,which is verified by constant and variable parameters. The results show that the improved identification method based on active power measurement is accurate. It has also very good adaptive when the variable parameters such as inertia time and flexibility factor is change.