Multi-Objective Design Optimization of Wind Turbine Blade Bearing

This paper focuses on augmenting the operational time of the wind power generation system through optimization of the blade bearing design. Blade bearing, alternatively recognized as pitch bearing, functions as the linkage between the hub and blades of the Wind Turbine (WT) rotor while permitting the suitable oscillation to regulate the power and loads of the WT. Artificial intelligence techniques like the Multi-Objective Genetic Algorithm (MOGA) and Multi-Objective Whale Optimization Algorithm (MOWOA) have been engaged simultaneously for maximizing the basic dynamic axial load rating and minimizing the bearing frictional loss. The proposed MOWOA is realized to be more competent in proffering worthier design solutions while compared with MOWOA.