A review of aeroelastic instabilities and resonance effects in wind turbine blade dynamics

Over the years, wind turbine blades have become increasingly larger and more flexible to achieve higher efficiency and lower energy costs, which brings more issues related to forced resonance and aeroelastic instabilities because of higher dynamic loads and complex inflow conditions. The manuscript systematically reviews the literature, covering experimental versus computational studies, reduced-order models (ROM), machine learning (MI) based aeroelastic models, Euler-Bernoulli beam models, Timoshenko beam models, geometrically exact beam formulations, and computational fluid dynamics (CFD) models coupled with structural dynamics models to investigate primary and internal resonances and dynamic stalls for National Renewable Energy Laboratory (NREL) 5-MW and International Energy Agency (IEA) 15-MW wind turbines. The article also addresses vibration mitigation techniques, including passive, active, and semi-active control, to resolve aeroelastic instabilities. Most studies have assumed linear aeroelastic models and isotropic blade material for initial structural dynamics analysis. The higher mode frequencies computed using the Euler-Bernoulli model differ by approximately 5.23%, those using the Timoshenko model by 3.13%, and those through the Rayleigh model by 3.4% from the geometrically exact formulations employed. Euler-Bernoulli models significantly overestimated flutter speeds compared to the geometrically exact beam model for the NREL 5-MW blades. A key takeaway is that modern, prolonged, flexible blades are sensitive to flutter instabilities, where aerodynamic damping can drop significantly at certain operational speeds. The Euler-Bernoulli beam model proved to be a valuable tool at the initial design stage due to its simplicity and computational efficiency. Future research on managing forced resonance and dynamic stalls in ultra-large blades should focus on integrating nonlinear modeling, cutting-edge materials and structures, artificial intelligence (AI)-powered digital twins, and exploring targeted active control techniques.