Soft Computing Techniques-Based Low Voltage Ride Through Control of Doubly Fed Induction Wind Generator

With increased penetration of Wind energy as a renewable energy source, grid codes worldwide necessitate those wind turbines (WT) should essentially be coupled to grid throughout as well as post fault conditions and must source reactive power to the grid with an objective of maintaining grid voltage. This chapter focuses on the Low Voltage Ride Through (LVRT) enhancement of Doubly fed induction generator (DFIG) wind turbine especially on the control of DFIG wind turbine and of its power converter. The main protection issues for DFIG wind systems during voltage transients are excessive currents flowing in the Rotor-Side Converter (RSC) and overvoltage in the dc-link capacitor of the partial scale back to back converter. Many DFIGs employ a crowbar-based system to shelter the converter at the rotor side during disturbed and/or distorted grid voltage circumstances. Although it helps in protecting the generator, it does not provide an appropriate grid support behavior. This shortcoming led to designing a new coordinated controller that excludes or even cancels the need for a crowbar. This chapter proposes a fault confrontation controller (FCC) design to augment the feature of low voltage ride through (LVRT) in this turbine. Considering the system’s nonlinear nature, an attractive Fault Confrontation Controller was constructed using computational intelligence (CI) techniques, namely fuzzy logic, backpropagation network (BPN), and adaptive neuro-fuzzy inference system (ANFIS). The simulation study demonstrates that the ANFIS system gives the best results for the proposed system.