Control Strategy for DFIG Wind Turbine in Variable Speed Wind Power Generation

The global electrical energy consumption is rising and there is steady increase of the demand on power generation. In addition to conventional power generation units a large number of renewable energy units are being integrated into the power system. The Wind Energy Conversion system (WECS) is the most cost competitive of all the environmentally clean and safe renewable energy sources in world. Doubly fed induction generator (DFIG) based wind farm is today the most widely used concept. In this paper, Artificial Neural Network (ANN) control technique has been developed for Doubly Fed Induction Generator (DFIG) based wind energy generation system. With the increasing use of wind power generation, it is required to instigate the dynamic performance analysis of Doubly Fed Induction Generator under various operating conditions. In this paper, two control techniques have been proposed, the first one is using PI controller and the second one is based on ANN. The performance of the proposed control techniques is demonstrated through the results. From the results it is observed that the dynamic performance of the DFIG is improved with the ANN control technique.