Parameter identification method for doubly fed fan based on improved sparrow algorithm

With the expansion of wind power grid integration and the promotion of the "dual carbon" goal, the modeling and parameter identification of doubly fed wind turbine control systems become increasingly important. A control parameter identification method for doubly fed induction generators (DFIGs) based on improved sparrow search algorithm (ISSA) is proposed to address the problem of difficulty in accurately characterizing the output characteristics of DFIGs under random wind speeds. Firstly, a model of the DFIG was constructed and key control parameters were selected. Subsequently, based on the ISSA algorithm, significantly enhancing identification accuracy and convergence speed. The simulation results show that the ISSA algorithm performs better in DFIG control parameter identification compared to particle swarm optimization (PSO) and the original sparrow algorithm (SSA).