INTERNATIONAL JOURNAL of RENEWABLE ENERGY RESEARCH K. Naresh et al., Vol.10, No.3, September, 2020 Control of DFIG Based Wind Turbine with Hybrid Controllers K. Naresh* ‡ , P. Umapathi Reddy**, P. Sujatha***, Ch. Rami Reddy**** *EEE Department, Research Scholar, JNTUA Ananthapuramu, Ananthapuramu, A.P- India- 515002 **EEE Department, Professor, SVEC- Thirupathi, A.P- India- 517102 ***EEE Department, Professor, JNTUA Ananthapuramu, Ananthapuramu, A.P- India- 515002 **** EEE Department, Koneru Lakshmaiah Education Foundation, AP, India. - 522502 (naresh5kelothu@gmail.com, moni_uma@yahoo.co.in, psujatha1993@gmail.com, crreddy229@gmail.com) ‡ Corresponding Author: K. Naresh, Research Scholar, EEE Department, JNTUA Ananthapuramu, A.P- India- 515002 Tel: +91 9949257091, naresh5kelothu@gmail.com Received: 31.05.2020 Accepted:22.06.2020 Abstract- There have been a few areas still suffering with the problem of huge power interruptions and power quality problems due to the enormous problems on the grid side and also there exists some areas suffering with lack of grid connection. A solution is required to avoid these power problems and providing grid independency for continuous power supply. The solution and an alternative to the main grid is the microgrid with the utilization of the renewable sources. This paper presents the design of wind turbine system with the usage of Doubly Fed Induction Generator (DFIG) as the power generating system which can be operated in grid-connected mode or in grid disconnected mode based upon the requirement. The DFIG enhances the transfer of power through the stator and also through the rotor, where the parameters like torque, DC link voltage and power of the system have been controlled with the two different hybrid controllers like neural network with PID controller and neural network with the predictive controller. A comparison has been provided between the performance of hybrid controllers in terms of DC link voltage and frequency of the supply. The system was realized and the results have been verified by using MATLAB Simulink. Keywords: Doubly Fed Induction Generator (DFIG), Neural Network with PID controller, Neural Network with Predictive Controller. 1. Introduction The utilization of renewable energy sources provides huge advantages like an unrestricted, readily existing and environmentally non pollutant. Especially the integration of renewable sources to the main grid can be called as a micro grid provides reliable, efficient and uninterrupted power supply to the consumers. The micro grid can be operated in islanded mode of operation reducing burden on the conventional grid or can also be operated in connection with the conventional grid providing supply to the grid incase of disturbances in the grid. This enhances the use of microgrid for local areas and obtaining the continuous power supply with the use of different types of energy sources [1]. Among the numerous available sustainable energy sources, the wind energy especially has the advantage of non investment of collecting the source and availability of source everywhere in the universe [2]. But the usage of wind has been existing from the few years with the help of horizontal and vertical axis wind turbine using fixed speed conversion systems [3] which involves the disadvantages of power supply only from the rotor, high mechanical stress, requires larger gearboxes, no controlling of voltage transmitted to grid. This can be reduced with the choosing of variable speed conversion systems which provides the transfer of power with the variation of speed. Among the numerous variable speed systems, DFIG has been chosen which is capable of transferring power through the stator [4-6] and also through the rotor and the power can be utilized efficiently from both sides. But there has to be a converter at the rotor to enable the power flow through the converter and power will be transferred to the stator directly. And to transfer the power at the rotor, two back to back converters named as rotor side converter and grid side converter has been chosen[33]. To