Parameter Identification of Grid-Forming Doubly-Fed Wind Turbine Generators Based on Disturbance Shielding and Multi-Objective Weighted Sum

This paper proposes a parameter identification strategy based on disturbance shielding and multi-objective weighted sum for grid-forming doubly-fed wind turbine generators. First, through parameter sensitivity analysis, the impact of control parameters on output characteristics is clarified, and a multi-disturbance application and shielding scheme for machine-side and grid-side controllers is designed to reduce parameter coupling and improve identification accuracy. Second, an improved alpha evolutionary algorithm with chaotic initialization and adaptive mutation is introduced to efficiently identify control parameters. Simulation results show that compared to the traditional primary-side short-circuit fault identification strategy, the proposed method significantly improves parameter identification accuracy under both steady-state and dynamic conditions.