Model-Based Predictive Control Applied to the Doubly-Fed Induction Generator Direct Power Control

Abstract

This paper proposes a model-based predictive controller for doubly-fed induction generator direct power control. The control law is derived by optimization of an objective function that considers the control effort and the difference between the predicted outputs (active and reactive power) and the specific references, with predicted outputs calculated using a linearized state-space model. In this case, the controller uses active and reactive power loop directly for the generator power control. Because the generator leakage inductance and resistance information were required for this control method, the influence of the estimation errors for these parameters was also investigated. Simulation results are carried out to validate the proposed controller.