Among eco-friendly forms of renewable energy, wind energy is a considerable one. In comparison with other energy sources, wind energy generally has less impact towards environment. There is no emission released which are harmful to environment, also it does not require water for cooling. The use of wind turbines also reduces the amount of energy generated by fossil fuels, reducing air pollution and carbon dioxide emissions. In order to provide grid supply with improved efficiency, a doubly fed induction generator (DFIG) and a wind turbine are used in this study. The effective functioning of the DFIG is accomplished by dq theory based Cascaded ANN which provides the rotor and grid side control. In order to convert the AC supply to DC, PWM rectifier is deployed, from which the energy is stored in super capacitor in DC form. A PWM inverter is implemented in order to change the supply from DC to AC when needed and reduces the harmonic using LC filter. The proposed DFIG system with neural network based control supplies stabilized voltage to the 3φ grid for various applications. The proposed system is simulated using MATLAB and efficient responses are obtained. © 2023 Elsevier B.V., All rights reserved.