Wind energy has emerged as one of the fastest growing renewable energy sources since mid-80‘s due to its low cost and environmentally friendly nature compared to conventional fossil fuel based power generation. Current technologies for the design and implementation of wind energy conversion systems (WECSs) include induction generator and synchronous generator based units. The doubly fed induction generator (DFIG) is chosen in this thesis because of its economic operation, ability to regulate in sub-synchronous or super-synchronous speed and decoupled control of active and reactive powers. Among the major challenges of wind energy conversion system, extraction of maximum power from intermittent generation and supervision on nonlinear system dynamics of DFIG-WECS are of critical importance. Maximization of the power produced by wind turbine is possible by optimizing tip-speed ratio (TSR), turbine rotor speed or torque and blade angle. The literature reports that a vast number of investigations have been conducted on the maximum power point tracking (MPPT) of wind turbines. Among the reported MPPT control algorithms, the hill climb search (HCS) method is typically preferred because of its simple implementation and turbine parameter-independent scheme. Since the conventional HCS algorithm has few drawbacks such as power fluctuation and speed-efficiency trade-off, a new adaptive step size based HCS controller is developed in this thesis to mitigate its deficiencies by incorporating wind speed measurement in the controller. In addition, a common practice of using linear state-feedback controllers is prevalent in speed and current control of DFIG-based WECS. Traditional feedback linearization controllers are sensitive to system parameter variations and disturbances on grid-connected WECS, which demands advanced control techniques for stable and efficient performance considering the nonlinear system dynamics. An adaptive backstepping based nonlinear control (ABNC) scheme with iron-loss minimization algorithm for RSC control of DFIG is developed in this research work to obtain improved dynamic performance and reduced power loss. The performance of the proposed controller is tested and compared with the benchmark tuned proportional-integral (PI) controller under different operating conditions including variable wind speed, grid voltage disturbance and parameter uncertainties. Test results demonstrate that the proposed method exhibits excellent performance on the rotor side and grid side converter control. In addition, the compliance with the modern grid-code requirements is achieved by featuring a novel controller with disturbance rejection mechanism. In order to reduce the dependency on system‘s mathematical model, a low computational adaptive network fuzzy interference system (ANFIS) based neuro-fuzzy logic controller (NFC) scheme is developed for DFIG based WECS. The performance of the proposed NFC based DFIG-WECS is tested in simulation to regulate both grid and rotor side converters under normal and voltage dip conditions. Furthermore, a new optimization technique known as grey wolf optimization (GWO) is also designed to regulate the battery power for DFIG driven wind energy system operating in standalone mode.

In order to verify the effectiveness of the proposed control schemes, simulation models are designed using Matlab/Simulink. The proposed model for MPPT and nonlinear control of grid-connected mode and GWO based power control of standalone DFIG-WECS has been successfully implemented in the real-time environment using DSP controller board DS1104 for a laboratory 480 VA DFIG. The comparison among different controllers suggests that each control technique has its own specialty in wind power control application with specific merits and shortcomings. However, the PI controller provides fast convergence, the ANFIS based NFC controller has better adaptability under grid disturbances and ABNC has moderate performance. Overall, the thesis provides a detailed overview of different robust control techniques for DFIG driven WECS in grid-connected and standalone operation mode with practical implementation.