High-fidelity aeroelastic analyses of wind turbines in complex terrain: fluid–structure interaction and aerodynamic modeling

Abstract

Abstract. This paper shows high-fidelity fluid–structure interaction (FSI) studies applied to the research wind turbine of the WINSENT (Wind Science and Engineering in Complex Terrain) project. In this project, two research wind turbines are going to be erected in the south of Germany in the WindForS complex-terrain test field. The FSI is obtained by coupling the CFD URANS–DES code FLOWer and the multiphysics FEM solver Kratos Multiphysics, in which both beam and shell structural elements can be chosen to model the turbine. The two codes are coupled in both an explicit and an implicit way. The different modeling approaches strongly differ with respect to computational resources, and therefore the advantages of their higher accuracy must be correlated with the respective additional computational costs. The presented FSI coupling method has been applied firstly to a single-blade model of the turbine under standard uniform inflow conditions. It could be concluded that for such a small turbine, in uniform conditions a beam model is sufficient to correctly build the blade deformations. Afterwards, the aerodynamic complexity has been increased considering the full turbine with turbulent inflow conditions generated from real field data, in both flat and complex terrains. It is shown that in these cases a higher structural fidelity is necessary. The effects of aeroelasticity are then shown on the phase-averaged blade loads, showing that using the same inflow turbulence, a flat terrain is mostly influenced by the shear, while the complex terrain is mostly affected by low-velocity structures generated by the forest. Finally, the impact of aeroelasticity and turbulence on the damage equivalent loading (DEL) is discussed, showing that flexibility reduces the DEL in the case of turbulent inflow, acting as a damper that breaks larger cycles into smaller ones.

Grand challenges in the design, manufacture, and operation of future wind turbine systems

“…Whereas a comprehensive discussion of these methods is beyond the current scope, the intent here is to examine the future role of HFM and transition to artificial intelligence and machine-learning methods to extract key phenomena for integration into lower-order models more suitable for future design and control applications. Validated computational models running the gamut from truly predictive and computationally intensive high-fidelity simulation for scientific inquiry (Sprague et al, 2020;Grinderslev et al, 2021;Guma et al, 2022) to computationally parsimonious resource models used in design and optimization workflows are now essential in assessing the complex inflow and structural interactions with modern turbine architectures . Although wind turbine technology and the understanding of the underlying physical phenomena driving turbine performance and loading has matured considerably (Haupt et al, 2019), coupled physics considerations across a wide range of spatial and temporal scales and combined external physical drivers (e.g., from wind, waves, and currents in offshore systems) make design and optimization at the turbine and wind plant levels challenging.…”

Multi-fidelity, steady-state aeroelastic modelling of a 22-megawatt wind turbine

“…However, to correctly predict the power performance of a rotor, fully coupled aero-elastic modelling is needed for modern rotors, which is usually referred to as fluid structural interaction (FSI). Several works exist that carry out FSI simulations on wind turbine rotors, some with application to operational cases [10,11] and others focusing on complex off-design standstill cases [12,13], and generally focus on time domain simulations. To make 3D CFD-based FSI tractable in a design context, in which blade design candidates are continuously assessed, the FSI solution process should ideally not incur computational overhead relative to a standard steady-state CFD solution.…”

Transforming Laser-Scanned 750 kW Turbine Surface Geometry Data into Smooth CAD for CFD Simulations

“…The site features four 100 m meteorological masts and two 750 kW wind turbines with a 72 m hub height and 50 m rotor diameter. Its planing and installation results from a significant ammount of over over many years through projects such as LIDARcomplex, KonTest and WINSENT [1,2]. It now provides real-world aerodynamic and meteorological data such as live transient loads, deformations, and power.…”