An Implicit Controlling of Adaptive Neuro Fuzzy Inference System Controller for The Grid Connected Wind Driven PMSG System

Abstract

The article presents the design and control of the adaptive neuro fuzzy Inference system (ANFIS) for the wind-driven permanent magnet synchronous generator (PMSG) in the grid connected system. The rectifier and inverter are connected with the PMSG output and the grid for maintaining the voltage at the grid under variable wind operations. Such interconnections have many challenges, like high harmonics at the output and an improper voltage profile. The harmonics are measured in terms of total harmonic distortion (THD). Performance parameters like peak overshoot and settling time of DC link voltage and rotor speed have been measured. The control of the rectifier and inverter has been assessed with the ANFIS and PID controllers. A closed strategic mechanism has been developed for the ANFIS and PID controllers for improving the performance parameters and harmonics.. Finally, it is observed that the peak overshoot (%) and settling time (sec) of the DC link voltage with ANFIS are 5.2% and 2.9 sec, which are found to be less in comparison to the PID controller with the values of 6.1% and 3.8 sec and other existing methods. Similarly, the settling time (sec) of rotor speed with ANFIS is 1.1 sec, which is less than the settling time (2.6 sec) of the PID controller. Another advantage of ANFIS is the reduction of THD (%) of 5.1% with respect to THD (%) of PID controllers of 6.2% and other existing methods. The reduced THD shows the improved version of the voltage profile.