Review of the Intelligent Frameworks for Pitch Angle Control in Wind Turbines

Abstract

Among the renewable energy sources, wind energy plays a crucial role in meeting the increasing global demand for clean energy. The variability in energy production makes wind turbines produce intermittent and varying power resources, variable mechanical loads, and a non-linear dynamic. The primary parameters to be controlled in wind turbines are the blade pitch angle and the generator torque. The challenges in designing the pitch controller include various non-linearities of wind turbines, constraints on pitch angle and its rate, and the stochastic nature of wind speed and unstructured model dynamics. Therefore, effectively addressing these complexities is important to ensure the stability and safety of a wind turbine. Existing literature extensively covered various control technologies applied to wind turbine systems, highlighting the diverse control methodologies and their applicability. However, there is limited evidence of the existing review papers focusing on applying intelligent control approaches to the collective pitch regulation of wind turbines. A comprehensive survey of the intelligent control approaches in collective pitch regulation was presented in this paper. It highlights the advantages of intelligent control strategies over traditional control methods in mitigating the challenges posed by system non-linearities. These approaches significantly enhance the performance of the wind energy generation system. Moreover, this paper presents the critical assessment areas for effective wind farm development and corresponding grid integration. This, in turn, will facilitate the growth of wind power utilization and assist researchers and engineers in integrating wind energy into the grid.

Keywords

• Collective pitch control
• intelligent control
• overview
• sustainable development
• wind farms
• machine learning