# Parametric study of the floating wind turbine configurations most likely to impact far-wake dynamics by OpenFAST

Muhammad Abdullah, Vincent Leroy, Sandrine Aubrun

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Muhammad Abdullah, Vincent Leroy, Sandrine Aubrun. Parametric study of the floating wind turbine configurations most likely to impact far-wake dynamics by OpenFAST. Wind Energy Science Conference, European Academy of Wind energy; Centrale Nantes, Jun 2025, Nantes, France. hal-05387070

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# Parametric study of the floating wind turbine configurations most likely to impact far-wake dynamics by OpenFAST

Muhammad Abdullah<sup>a,b</sup>, Vincent Leroy<sup>a</sup>, Sandrine Aubrun<sup>a</sup>

<sup>a</sup> Nantes Université, École Centrale Nantes, CNRS, LHEEA, UMR 6598, F-44000 Nantes, France

<sup>b</sup> Department of Wind Energy, Technical University of Denmark (DTU), Frederiksborgvej 399, 4000 Roskilde, Denmark

E-mail: sandrine.aubrun@ec-nantes.fr

*Keywords:* Floating Wind Turbine (FWT), floating motion, wake dynamics,

## 1. Introduction and Research Background

The growth of installation for offshore wind farms (OWFs) have increased significantly recently, for example, installed capacity of commissioned OWFs worldwide was noted as 64.3 GW at the end of 2022 [1], and aim is to reach 100 GW by 20230 [2]. Particularly, to make installation of offshore wind farms successful, recently several tests have been performed on stand-alone FOWT as demonstration projects. Moreover, installation of FOWTs is evolving from single turbine setup to small arrays consisting a few turbines, as demonstrated by the recent projects such as Hywind Scotland (5 turbines with 6MW capacity, installed in 2017) and the WindFlaot Atlantic (3 turbines with 8MW capacity, installed in 2020). Furthermore, several other floating offshore wind farms (FOWFs) are under planning stages, and a large-scale floating OWFs consisting of multiple-arrays of FOWTs are anticipated to be installed in near future. With this transition to full operational FOWFs, understanding wake behaviour, effect of floating motions on wake characteristics, and modelling of wake interactions between FOWTs are becoming crucial and highly-relevant to design of FOWTs and to enhance power production [3].

The present research question is to find the mutual interactions of platform motions and wake characteristics. Hence, there is need of an extensive study comparing impact of platform motions on wakes for different turbine sizes, with different floater concepts under different wave, wind and turbulence intensity conditions. This research work has main objective to investigate platform motion's as well as combination of turbine and floater, which are more prone to impact, through a linear response, far-wake meandering and pulsation downstream of the FOWT.

## 2. Methodology

Three different floater concepts (tension leg platform, spar and semi-submersible) for NREL-5MW and spar floater concept for DTU-10 MW and UMaine semi-submersible floater concept for IEA-15MW wind turbine were chosen to study floating motions effect on wake characteristics using OpenFAST tool. Several environmental conditions were studied; one corresponds to IEC standards and one to realistic one taken from Life50+ project [4] for site C (West of Barra (WoB)). The Life50+ project does not provide the turbulence intensity and power law coefficient of the vertical profile's information for average wind speed, therefore, these values were chosen from the SEM-REV site [5] which is a sea test site in France. Even though, each studied floating platform has been designed for different water depth conditions, however, same environmental conditions were studied in this research work.

Two wind speeds of 8 m/s (below rated) and 14 m/s (above rated) were used to investigate how floating motion changes with different wind speeds within different regions of turbine's operational curve. Two turbulence levels (IEC and WoB conditions) were selected to analyse platform motions under IEC standard conditions and realistic conditions of WoB site. The turbulence intensity and IEC-windtype were chosen as Class C and normal respectively for IEC conditions. Four wave conditions (from WoB site) varying from normal to severe were chosen for both wind speeds to analyse response of floater motions under different wave conditions and consequently their potential effects on wake dynamics. The significant wave height (Hs) and peak period (Tp) were chosen as the most probable values from the joint probability distribution of wind and wave conditions at the WoB site for the studied wind conditions. The irregular waves were studied with JOWNSWAP spectrum, keeping heading angle 0°. Power law was used to extrapolate the wind data with the wind shear component for IEC conditions as 0.14, which is aligned with the IEC standard conditions and IEC neutral atmospheric stability conditions, whereas wind
<figure><img src="image_3.png" /></figure>

shear component for WoB site was 0.11, which was computed from data of SEM-REV site in France. The details of environmental conditions for both IEC and WoB site are presented in Table 1. Turbsim tool was used to generate synthetic wind fields using Kaimal turbulence model. The coherence decrement parameter (a) and coherence offset parameter (b) were computed using standard IEC model (61400-1 3rd edition), yielding values of a = (12, 12, 12, 12) and b = (3.53E-04, 0, 0) for velocity components (u, v, w), respectively. This configuration for b did not induce accurate wake dynamics, therefore, the values of b for v, and w components were adjusted to match that of u value.

<table><caption>Table 1. Environmental Conditions</caption><thead><tr><th>Wind (m/s)</th><th>Hs (m)</th><th>Tp (sec)</th><th>TI (%)- NREL 5MW</th><th>TI (%) - DTU 10MW</th><th>TI (%) - IEA 15MW</th></tr></thead><tbody><tr><td rowspan="4">8 (14)</td><td>1.5</td><td>8</td><td></td><td></td><td></td></tr><tr><td>2.5</td><td>9.5</td><td>4.9 (5.86)</td><td>4.8 (5.69)</td><td>4.7 (5.46)</td></tr><tr><td>4</td><td>11</td><td>IEC Class C</td><td>IEC Class C</td><td>IEC Class C</td></tr><tr><td>5.5</td><td>12</td><td></td><td></td><td></td></tr></tbody></table>

## 3. Results and Discussion

<figure><img src="image_4.png" /><figcaption>Figure 1: Maximum PSDs for $f_{red} \le 0.5$ for different configurations of floater for surge (top) and yaw (bottom)</figcaption></figure>

Following Dynamic Wake Meandering (DWM) model assumptions, it is expected that far-wake dynamics are highly affected by external disturbances for reduced frequencies based on the rotor diameter ($f_{red} = \frac{f \times D}{U_{hub}}$) lower than
<figure><img src="image_5.png" /></figure>

0.5, whereas motions with reduced frequencies greater than 0.5 are expected to help in faster wake recovery. At low reduced frequencies, the surge is expected to generate a modulation of the velocity deficit, and so of the available power for a downstream wind turbine, whereas other motions are expected to generate wake meandering (yaw, heave, sway, roll), or combination of both phenomena (pitch). Schliffke et al. [6] conducted experimental study with a porous under imposed motion (surge, heave and pitch) and their results were in line with these assumptions. On the other hand, Messmer et al. [7] extended the investigations with a rotating wind turbine and for higher imposed reduced frequencies $f_{red} \in [0.55, 0.9]$ and observed a self-generated wake meandering at lower reduced frequencies, due to non-linear interactions.

The objective is to limit the parametric study to configurations where the linear response can be assumed ("lock-in" of the wake dynamics response on the excitation frequency). Therefore, this parametric study focuses on spectral content of platform motions only for ($f_{red} < 0.5$). The highest values of $PSD_{max}$ lie under $f_{red}$ values lower than 0.3, 0.3, 0.5, 0.5, 0.5, and 0.35 for surge, sway, heave, roll, pitch and yaw platform motions for all floaters. The surge motion has highest values of $PSD_{max}$ for all the studied wave and wind conditions, and floaters compared to other motions, this indicates that surge motion has higher potential to effect wake dynamics, followed by yaw platform motions as shown in Figure 1. Moreover, this study results that wake characteristics would be least affected by roll and heave motions. The semi-submersible floaters for NREL-5MW and IEA-15MW wind turbines have highest values of $PSD_{max}/D^2$ for surge (followed by spar + DTU-10MW) and of $PSD_{max}$ for sway, this depicts that the semi-submersible floaters have higher chances to impact dynamic wake properties.

The wake is more intense at below rated wind speeds because of higher thrust coefficient value compared to above rated ones (turbine blades are pitched to mitigate the aerodynamic performances). Hence, although this study results that generally higher platform motions are noticed at above rated wind speeds (14 m/s) compared to below (8 m/s), it does not mean that these larger platform motions can impact the wake dynamics at higher level. It will very much depend on the mechanisms responsible of the modifications of the wake dynamics (modification of the wake release location, wake deflection due to rotor misalignment, etc.). Higher values of $PSD_{max}$ for platform motion are observed for IEC wind conditions compared to WoB for most of the platform's geometries and their motions, because IEC conditions have higher turbulence intensities, which can lead to higher platform motions.

## 4. Conclusion and Future Remarks

Parametric study concluded following ranking for platform motions from highest to lowest probability to affect the far-wake dynamics through a linear response under 0.5 values of $f_{red}$.

$$ \text{Surge} > \text{Yaw} > \text{Sway} > \text{Pitch} > \text{Heave} > \text{Roll} $$

Parametric analysis also concluded following combination of Turbine and floater from highest ranking to lowest.

$$ \begin{array}{l} \text{IEA-15MW (Semi-Submersible)} \approx \text{NREL-5MW (Semi-Submersible)} > \text{DTU-10MW (Spar)} \approx \text{NREL-5MW (Spar)} > \text{NREL-5MW (TLP)} \end{array} $$

Moreover, imposed motion cases (surge, heave and pitch) were studied to check ability of FAST.Farm to reproduce wake meandering effects in later portion of the research. A natural progression of this work is to analyse wake centre positions at different downstream distances for the resulted combinations.

## 5. References

[1] Wang K, Chen S, Chen J, Zhao M, Lin Y. Study on wake characteristics of fixed wind turbines and floating wind turbines arranged in tandem. Ocean Engineering. 2024;304:117808.

[2] Soares-Ramos EPP, de Oliveira-Assis L, Sarrias-Mena R, Fernández-Ramírez LM. Current status and future trends of offshore wind power in Europe. Energy. 2020;202:117787.

[3] Carmo L, Jonkman J, Thedin R. Investigating the interactions between wakes and floating wind turbines using FAST.Farm. Wind Energ Sci Discuss. 2024;2024:1-32.

[4] Yu W, Müller K, Lemmer F. Qualification of innovative floating substructures for 10 MW wind turbines and water depths greater than 50 m. LIFES50+. 2018.

[5] Thilleul Olivia, & Perignon Yves. (2022). SEM-REV Metocean design basis (1.3). Zenodo. https://doi.org/10.5281/zenodo.6325718

[6] Schliffke B, Aubrun S, Conan B. Wind tunnel study of a "floating" wind turbine's wake in an atmospheric boundary layer with imposed characteristic surge motion. Journal of Physics: Conference Series, vol. 1618. IOP Publishing; p. 062015.

[7] Messmer T, Hölling M, Peinke J. Enhanced recovery caused by nonlinear dynamics in the wake of a floating offshore wind turbine. Journal of Fluid Mechanics. 2024;984:A66. doi:10.1017/jfm.2024.175