Encoderless Model Predictive Control of Doubly-Fed Induction Generators in Variable-Speed Wind Turbine Systems

Abstract

In this paper, an encoderless finite-control-set model predictive control (FCS-MPC) strategy for doubly-fed induction generators (DFIGs) based on variable-speed wind turbine systems (WTSs) is proposed. According to the FCS-MPC concept, the discrete states of the power converter are taken into account and the future converter performance is predicted for each sampling period. Subsequently, the voltage vector that minimizes a predefined cost function is selected to be applied in the next sampling instant. Furthermore, a model reference adaptive system (MRAS) observer is used to estimate the rotor speed and position of the DFIG. Estimation and control performance of the proposed encoderless control method are validated by simulation results for all operation conditions. Moreover, the performance of the MRAS observer is tested under variations of the DFIG parameters.