Doubly Fed Induction Generator Based Wind Turbine with Adaptive Neuro Fuzzy Inference System Controller

2013 ◽  
Vol 7 (1) ◽  
pp. 45-55 ◽  
Author(s):  
Nallavan Govindaraj ◽  
Dhanasekaran Raghava .
2019 ◽  
Vol 44 (2) ◽  
pp. 125-141
Author(s):  
Satyabrata Sahoo ◽  
Bidyadhar Subudhi ◽  
Gayadhar Panda

This article presents a multiple adaptive neuro-fuzzy inference system-based control scheme for operation of the wind energy conversion system above the rated wind speed. By controlling the pitch angle and generator torque concurrently, the generator power and speed fluctuation can be reduced and also turbine blade stress can be minimized. The proposed neuro-fuzzy-based adaptive controller is composed of both the Takagi–Sugeno fuzzy inference system and neural network. First, a step change in wind speed and then a simulated wind speed are considered in the proposed adaptive control design. A MATLAB/Simulink model of the wind turbine system is prepared, and simulations are carried out by applying the proportional integral, fuzzy-proportional integral and the proposed adaptive controller. From the obtained results, the effectiveness of the proposed adaptive controller approach is confirmed.


2015 ◽  
Vol 40 (3) ◽  
pp. 135-143
Author(s):  
Mohanad A. Deif ◽  
Mohamed A. A. Eldosoky ◽  
Hesham W. Gomma ◽  
Ahmed M. El-Garhy ◽  
Ahmed S. Ell-Azab

Sign in / Sign up

Export Citation Format

Share Document