%0 Journal Article %T Control of Pitch Angle in Wind Turbine Based on Doubly Fed Induction Generator Using Fuzzy Logic Method %J Journal of Renewable Energy and Environment %I Materials and Energy Research Center (MERC) Iranian Association of Chemical Engineers (IAChE) %Z 2423-5547 %A Hosseini, Ehsan %A Behzadfar, Neda %A Hashemi, Mahnaz %A Moazzami, Majid %A Dehghani, Majid %D 2022 %\ 01/11/2022 %V 9 %N 2 %P 1-7 %! Control of Pitch Angle in Wind Turbine Based on Doubly Fed Induction Generator Using Fuzzy Logic Method %K Doubly Fed Induction Generator (DFIG) %K Fuzzy Logic Controller %K PI controller %K pitch angle %K Wind Turbine %R 10.30501/jree.2021.293546.1226 %X Wind turbines can be controlled by controlling the generator speed and adjusting the blade angle and the total rotation of a turbine. Wind energy is one of the main types of renewable energy and is geographically extensive, scattered and decentralized and is almost always available. Pitch angle control in wind turbines with Doubly Fed Induction Generator (DFIG) has a direct impact on the dynamic performance and oscillations of the power system. Due to continuous changes in wind speed, wind turbines have a multivariate nonlinear system. The purpose of this study is to design a pitch angle controller based on fuzzy logic. According to the proposed method, nonlinear system parameters are automatically adjusted and power and speed fluctuations are reduced. The wind density is observed by the fuzzy controller and the blade angle is adjusted to obtain appropriate power for the system. Therefore, the pressure on the shaft and the dynamics of the turbine are reduced and the output is improved, especially in windy areas. Finally, the studied system is simulated using Simulink in MATLAB and the output improvement with the fuzzy controller is shown in the simulation results compared to the PI controller. Fuzzy control with the lowest cost is used to control the blade angle in a wind turbine. Also, in this method, the angle is adjusted automatically and it adapts to the system in such a way that the input power to the turbine is limited. Compared to the PI controller, by calculating different parameters, the power quality for fuzzy controller is enhanced from 2.941 % to 4.762 % for wind with an average speed of 12 meters per second. %U https://www.jree.ir/article_143158_c61b2c3b1579d9e1ed51fd90374b2be3.pdf