The wake of a wind turbine can influence the wind turbines located downstream in a wind farm, leading to lower power generation and a decreased lifetime. Therefore, analyzing the wake characteristics is essential for a better alignment of wind turbines in a wind farm and more accurate yield predictions. The goal of this specific PhD project is to improve the understanding of wave and ABL-like wind on the wake characteristics of the IEA 15 MW floating wind turbine. The objectives are: designing a porous disc representing the IEA 15 MW turbine immersed in ABL, simulations with OpenFast to obtain platform motion and to determine the requirements for a hexapod capable of doing relatively small and high frequent motions, investigating the effects of wind/wave coupling on wake characteristics of the IEA 15 MW wind turbine placed on VolturnUS-S platform, and examining the wake effects in floating wind farms. This PhD work will lead to a safer and more reliable increase in the sustainable energy supply by investigating the characteristics of larger floating offshore wind turbines. The generated dataset can be used to optimize the layout of a floating wind farm. In addition, the PhD work will create more knowledge on the hybrid testing itself.