Proceedings of the Thirty-second (2022) International Ocean and Polar Engineering Conference
Shanghai, China, June 5–10, 2022
Copyright © 2022 by the International Society of Offshore and Polar Engineers (ISOPE)
ISBN 978-1-880653-81-4; ISSN 1098-6189

www.isope.org

Wake effects on dynamics of two semi-submersible wind turbines with varying hub heights
Xiaosen Xu(1), Jiayang Gu(1), Lin Du(2), Puyi Yang(3), Fangxin Hu(1)Jiangsu University of Science and Technology, Zhenjiang, Jiangsu, China
Ningbo University, Ningbo, Zhejiang, China
Florida Institute of Technology, Melbourne, Florida, United StatesABSTRACT

turbulence intensity in the form of a wake. Intensified turbulence may
result in increased fatigue stresses on downstream FWTs. For
downstream turbines, wake interactions enhance structural turbulenceloading, hence raising fatigue loads and limiting turbine lifespan. Bothwind farm power output and turbine lifetime are critical factors inevaluating wind energy's profitability. A deeper understanding of wakeinference in the wind farm enables the identification of how
interactions impact downstream turbines, which might result inincreased turbine performance and lifespan via improved yaw control
and micro-sitting placement. Figure 1 illustrates the wake phenomenon
in the offshore wind farm.

Wind farms are typically composed of a single model of turbine withidentical hub heights. The wind field behind the turbine in a wind farm
has a lower mean wind speed and a greater turbulence intensity than theambient wind field. As turbines get larger in size, the impact of wakeinterference between turbines becomes more substantial, particularly
for floating wind turbines (FWT). FAST.Farm is employed to simulatea two semi-submersible FWT (5MW & 15MW) case with two different
hub heights. The results demonstrates that wake effect has a noticeableinfluence on the movements and loads of downstream turbines.

KEY WORDS: Dynamic wake meandering; Varying hub
heights; Floating wind turbine; Fatigue.
NOMENCLATURE

Computational Fluid Dynamics
Damage-Equivalent Load
Dynamic Wake Meandering
Engineering Wake Models
Floating wind turbine
Large Eddy Simulations
National Renewable Energy Laboratory
Power spectrum density

CFDDEL
DWM
EWM
FWTLES
NRELPSD

Figure 1. Wakes in Horns Rev wind farm

INTRODUCTION

There are several modeling methodologies that may be used tocharacterize the wake region in general, ranging from Engineering
Wake Models (EWM) to Computational Fluid Dynamics (CFD). The
EWM model is computationally efficient and well-suited for simulating
a quasi-steady wake in terms of wind farm overall power production.
However, the EWM model is incapable of taking structural stresses into
account or capturing wake effects. CFD models are high-fidelity
simulations that use techniques such as Large Eddy Simulations (LES)and Reynolds Averaged Navier Stokes (RANS). LES models provide
the most accurate modeling of wake dynamics and may be used inconjunction with aero-hydro-servo-elastic simulation to examine theFWT's dynamics. However, LES models often incur a high computing
cost, making them prohibitively expensive at an iterative design stage.

Wind energy is a critical component of the growing renewable green
energy industrial sector within the offshore energy sector. Generally,
lower ocean surface roughness is related with increasing mean windspeeds. Wind resources are more plentiful in deep water where bottomfixed offshore turbines are impractical. Floating wind turbines (FWTs)
are a cost-effective way to gather wind energy in deep water. There are
numerous floating wind farms in the development stage, as well as one
that is operational, named Hywind Scotland. With the development
toward deep ocean wind energy harvesting, understanding wakeinteraction between FWTs becomes increasingly critical.
When upstream air flows over a wind turbine, the mean wake velocity
drops as the wake grows downstream of the rotor plane from energy
extraction. The wake created by turbines has a direct detrimental effecton the performance and lifetime of downstream turbines. This isbecause a wake velocity deficit limits power output while increasing

The Dynamic Wake Meandering (DWM) model requires lesscomputing than the LES model and may also be used in conjunction
with aeroelastic modeling tools. The DWM model is optimized forcapturing wake characteristics such as wake deficiency and wake

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