AI Based ANN Control of Double Fed Induction Generator Based Wind Power System

A Doubly Fed Induction Generator (DFIG) or wind energy conversion, is a most popular generator in industry which relies on wind farms. The DFIG's variable structure properties and nonlinearities enable a controller design for this type of system to a difficult task. Required dynamic behavior is constructed by, verifying effectiveness of suggested system and enhancing closed loop system's functionality, a unique method is proposed in this paper. To maintain DC connection at constant, a proportional integral PI controller is used. For grid synchronization Artificial Neural Network (ANN) controller is employed. By the deployment of D-Q model, the reference current is generated for of
$3\ \phi$
grid. The constant state power of the device at different wind speeds are considered to contribute to the ANN controllers' reliability. The
$3\phi$
Voltage Source Inverter (VSI) intended for regulate the control flow of grid voltage. Obtained results are verified using MATLAB platform. Trial results clearly demonstrated that the suggested strategy surpassed the conventional methods in terms of effectiveness, dependability and minimal ripples with a minimized THD value of 1.1%.