Performance Optimisation of a Wind Turbine Simulator with Transverse Cracked Blades using Taguchi-Based Grey Relational Analysis

The presence of blade surface cracks creates chances for vibration propagation that affects wind turbine performance. This study examines the effects of transverse cracks on the vibration levels and power output of wind turbine systems. Multiple regression models are developed as predictive tools to highlight the impact of transverse crack sizes and variations in rotational speed on vibration levels and power generation. Grey relational analysis is used as an optimisation technique to identify optimal settings for maximum power output and minimum vibration levels. By modelling and analysing these factors, the study reveals a significant correlation between increased crack size and elevated vibration levels, which can compromise structural integrity. Additionally, while higher rotational speeds initially boost power output, they also lead to exponential increases in vibration, exacerbating the risks associated with blade defects. The findings emphasise the critical need for a balanced approach in optimising turbine performance, introducing a novel approach to speed management and vibration control, which is employed in this study. The research suggests potential avenues for future exploration, including the development of advanced materials and design innovations aimed at mitigating these risks, enabling safer and more efficient turbine operation. KEYWORDS Defect, optimal settings, power, rotational speed, regression, vibration