This paper reviews the various control crowbar methods associated with doubly-fed induction generator (DFIG) wind energy system (WES) during power system faults. The crowbar control methods are designed to improve the fault ride-through (FRT) capability of DFIGs based on WESs. The adaptive neural-fuzzy inference system (ANFIS) is developed to detect the fault conditions and control the crowbar protection techniques. The proposed ANFIS crowbar protection technique detects the fault based on the measurement of the three phase voltages and currents at the terminals of the DFIG wind turbine (WT) to activate the crowbar protection system during fault period and deactivate it after fault clearance. Furthermore, the proposed ANFIS crowbar techniques are investigated to enhance the stability of studied WT generators and also, it designed to protect system components. All these simulations are carried for the model consists of 9 MW DFIG WTs connected to the grid model in Simulink/Matlab. Simulation results also revealed that outer terminal crowbar is more effective as compare with other crowbar techniques via ANFIS control strategy.