A new model implementation for doubly fed induction generator used in variable speed wind turbines

In this thesis, a new approach has been applied to the control of Doubly Fed Induction Generator (DFIG), which is generally used in variable speeds in wind turbines. Matrix Converter (MC) is implemented to the system due to many advantages, such as no need for high value filters, capability of bidirectional energy conversion and no need for DC bus. Nevertheless, modulation methods are very difficult and require high computational effort. Therefore, the Model Predictive Control (MPC) method has been improved to simplify the complexity of this topology. However, the weaknesses of this control method are that it uses a mathematical model and is affected by parameter changes caused by external disturbance, frequency and temperature variations. In this study, a reduced-order Extended Kalman Filter (EKF) has been also applied as an observer to eliminate the variations in the rotor resistance and stator resistance of the DFIG caused by frequency and temperature variations, sensor noise or uncertainties. Simulation studies have been carried out using Matlab / Simulink program. The algorithm is performed using TMS320F28335 Digital Signal Processor (DSP) that has a 32-bit floating point processor operating at 150 MHz. The results obtained from the experimental set-up are compared with the simulation results, and the performance of the proposed method is verified by IEEE and IEC Standards.