Estimating Wind Turbine's Pitch Angle for Smart Control in Hybrid Energy Network Under Random Loading Conditions

Amidst the ever-increasing global demand for energy, there has been a crucial shift towards incorporating green energy sources into conventional power grids, amplifying the complexity of these systems. This study delves into the intricate challenges of generation control within hybrid power networks, emphasizing wind farms as key contributors to green energy. In the dynamic environment of a wind farm-integrated hybrid power network with random loading patterns, the research introduces an innovative control strategy. This involves the precise estimation of optimal pitch angles and the fine-tuning of a fractional-order controller. This is executed using the firefly optimization (FFO) method to enhance overall generation control performance, fostering a more sustainable power infrastructure. The power generated by a wind turbine is intricately linked to the pitch angle of its blades. This angle plays a critical role in determining the aerodynamic forces acting on the blades and, consequently, the turbine's overall efficiency. The proposed approach is simulated using the MATLAB/SIMULINK tool.