PI Controller Design Using Neural Tuning Method for DFIG Grid Integration
R. R. Hete, Tarun Shrivastava, Ritesh Kumar Dash · 2024
A wind system with DFIG based turbine integrated with the existing grid, power flow in this system both real and reactive determined on different factors. This work includes a recurrent neural network based Neural Tuning Machine method for controlling flow of real and reactive power. Using this method, control on flow of reactive power from converter which is on the rotor side is proportionate to controller on the grid side through a coupling voltage. In order to regulate voltage regulation, control action depends on voltage profile at each bus location. The analysis in regards to DFIG configuration has been thoroughly examined in this paper. To control the parameters of inner current loop, this neural tuning machine is advantageous over traditional PI controller has been shown. To show the effectiveness of the control algorithm, the model is designed based on MATLAB Simulink for carrying out validation. All the findings and computations in this paper follow IEC and IEEE standards.