Dynamic equivalence of doubly-fed wind turbines based on parameter identification and optimization

The dynamic equivalence and modeling of large-scale wind farms is the basis for studying the problem of multi-temporal and spatial scale wind farms grid connection, and the establishment of a high-precision equivalence model is a key issue among them. This paper takes doubly-fed wind turbines as the research object. Aiming at the problem of large dynamic errors in direct aggregation of equivalents into a single unit, an equivalent model combined with particle swarm optimization algorithm is established to improve the accuracy of dynamic equivalents. The electrical parameters, reactive power reference values, active power controller parameters, and active DC voltage controller parameters are optimized using particle swarm optimization. The research results show that the equivalent model after optimizing the parameters of the active power and DC bus voltage controller is the closest to the detailed model in describing the dynamic characteristics of multiple machines.