Intelligent Pitch Angle Control Based on Gain-Scheduled Recurrent ANFIS

Abstract

The effective utilization of wind energy conversion system )WECS( is one of the most crucial concerns for the development of renewable energy systems. In order to achieve appropriate wind power, different pitch angle methods are used. Recurrent Adaptive Neuro-Fuzzy Inference System (RANFIS) is utilized in this paper in a new effective design to improve the performance of classical and adaptive Proportional Integral (PI) controllers applied for the pitch control purposes. Adaptive-online performance and high robustness coverage are the main advantages of the suggested controller. The effectiveness of the proposed method is verified by a simplified two-mass wind turbine model and a detailed aero-elastic wind turbine simulator (FAST7). At any given wind speed, the proposed controller has outperformed PI, Adaptive Neuro-Fuzzy Inference System (ANFIS), and RANFIS based controllers, reducing the mechanical stress of drive train while presenting suitable aerodynamic power tracking and maintaining the rotational speed of the rotor under the rated value.