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A Control Strategy for DFIG wind turbine using SLS-TLBO and fuzzy logic

Wind turbine systems need a suitable control system to achieve the best performance and efficiency during its operation, which is dependent on many unpredictable factors. Grid side and rotor side converters play a vital role in the system, hence they require suitable control algorithms and appropriate control parameters. In this paper control parameters is determined by smart line search enhanced by teaching-learning based optimization (SLS-TLBO) algorithm, which improves the reliability of the wind turbine system. To acquire the accurate input power control in a wide range of wind speed, drive train control system needs an appropriate pitch angle controller. In order to reach this goal fuzzy logic controller, which is well known for its capability in dealing with nonlinear systems is applied to pitch angle controller. A 30MW Doubly Fed Induction Generator (DFIG) wind turbine in connection with the IEEE 6 bus power system has been analyzed to validate the proposed control algorithms. The simulation result proves the accuracy of the controllers.