Wind tunnel inflow data assimilation in an LES digital twin for improving validation against an experimental wind turbine wake

Abstract

Abstract Wind energy is playing an essential role in the energy transition towards a carbon-neutral system, for which wind turbine wakes are one of the most important aspects. By extracting energy from the flow, the turbine generates power but also decreases the production and increases the loading of downstream wind turbines; and potentially affects nearby structures. To better understand the physical phenomenon, Large Eddy Simulation (LES) offers scale-resolving capabilities and a physical insight into complex turbulence flows. The state of the art in terms of high-fidelity wake simulations consists in combining LES with an Actuator Line Model in order to capture the tip vortices and detailed wake dynamics. This paper focuses on the comparison between such simulation, with experiments in the controlled environment of a wind tunnel, in order to assess the performance and limitations of the model. A large part is dedicated to reproducing a developing flow, with a controlled level of turbulence. The Recycle and Rescale Method is used to provide the mean inflow profile, while a novel approach using controlled volume forces allows to improve the turbulence level of the flow. With the proposed methodology, the mean profile is properly imposed, while the associated turbulence characteristics is improved by roughly 50 %.