Wind Turbine Active Power Control Based on Multi-Model Adaptive Control

This paper proposes a multiple model adaptive control method of wind turbine active power that considers the complexity of the control model, nonlinear and strong coupling. The model is designed to reduce the negative influences of wind turbines in the process of active power control caused by different uncertain factors. We first build the multiple model of turbine operating by using subtracting cluster algorithm, based on data of a 1.5MW doubly-fed inductor generators (DFIGs) in a wind farm in Gansu, China. We use recursive least squares (RLS) algorithm to identify local model parameters. In addition, the controller is designed by adopting online optimal control model which based on a weighted index of output matching switching strategy. The controller is to realize multi-model adaptive control (MMAC). Results show that the proposed method has good control performance. The method can effectively solve the problems of wind turbines nonlinear modeling and active power control in operation.