Development and Simulation of Adaptive Neuro Fuzzy Controller Based Pitch Angle Controlled DFIG System For Wind Turbine

Wind energy is clean and renewable, which will never be dried up. The development of wind power has drawn the attention of the world and the proportion of wind power in the grid is getting higher and higher. Nowadays, the mainstream model of the wind power generator (WTG) is doubly-fed wind power generator (DFIG). With more and more wind power generators connected to the grid, the safe and steady operation of the power system will be deeply influenced. Wind turbines can operate with either fixed speed or variable speed. For fixed speed wind turbines, the generator (induction generator) is directly connected to grid. Since the speed is about fixed to the grid, and mainly certainly not controllable, the turbulence of the wind will result in power variations, and thus affect the power quality of the grid. Modern high power wind turbines are capable of adjustable speed operation and use either singly-fed induction generator (SFIG) or doubly-fed induction generator (DFIG) systems. The DFIG technology allows extracting maximum energy from the wind for low wind speeds by optimizing the turbine speed, presently DFIG based wind turbines are quite popular as it can extract maximum power. Though the DFIG based wind turbines can able to provides maximum extent of power but greatly suffers from the power oscillation, to overcome this problem this paper proposes a novel adaptive neuro fuzzy controller (ANFIS) for efficient pitch angle control of DFIG system for wind power generation, so that the DFIG based wind turbines not only able to provide maximum power but the power obtained will be highly stable also, irrespective to the wind speed fluctuations. For the comparative analysis, a comparison is also presented between the conventional PI controller and proposed ANFIS based controller. The obtained result indicates that, the proposed method is highly efficient to sustain the power oscillations as compare to state of art techniques. In addition to this it is also found that, the proposed ANFIS based pitch angle controller takes 80% less settling time as compare to conventional PI controller. DOI: 10.17762/ijritcc2321-8169.15062