Research on Wake Characteristics of Dynamic Yawing Offshore Wind Turbine by Proper Orthogonal Decomposition

The wake that forms behind a yawing wind turbine is a complex flow region that can affect the performance of downstream turbines in offshore wind farms. It contains various flow features, including velocity deficit, shear layers, and vortex structures, which evolve in both time and space. Understanding this behavior is important for the design and operation of large-scale offshore wind farms. In this work, large-eddy simulations combined with proper orthogonal decomposition are used to study the wake development behind the National Renewable Energy Laboratory five-megawatt offshore wind turbine under both aligned and yawed inflow conditions. The results indicate that yawing the rotor leads to a lateral shift in the wake and increased asymmetry, with a stronger shear layer forming on one side. This asymmetry promotes enhanced mixing between the wake and the surrounding flow, contributing to a faster downstream recovery of the velocity field. The proper orthogonal decomposition analysis shows that the most energetic modes are associated with large-scale wake deflection and meandering, while higher-order modes correspond to smaller and less stable flow structures within the shear layer. The temporal evolution of these modes illustrates how the wake responds to the yaw maneuver and gradually reaches a new quasi-steady state. Overall, the study provides insight into the influence of yaw on wind turbine wake dynamics and demonstrates the applicability of combining large-eddy simulation with proper orthogonal decomposition for wake analysis in offshore wind farm studies.

Authors

Institutions

Publication Details

Journal
Oceans
Published
2026-03-09
DOI
https://doi.org/10.3390/oceans7020025
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research on Wake Characteristics of Dynamic Yawing Offshore Wind Turbine by Proper Orthogonal Decomposition

Longyan Wang, Bowen Zhang, Jie Ge, Oussama Sabbar
Oceans
Wind Energy Research and Development
article

Research on Wake Characteristics of Dynamic Yawing Offshore Wind Turbine by Proper Orthogonal Decomposition

Longyan Wang, Bowen Zhang, Jie Ge, Oussama Sabbar
article en

Abstract

The wake that forms behind a yawing wind turbine is a complex flow region that can affect the performance of downstream turbines in offshore wind farms. It contains various flow features, including velocity deficit, shear layers, and vortex structures, which evolve in both time and space. Understanding this behavior is important for the design and operation of large-scale offshore wind farms. In this work, large-eddy simulations combined with proper orthogonal decomposition are used to study the wake development behind the National Renewable Energy Laboratory five-megawatt offshore wind turbine under both aligned and yawed inflow conditions. The results indicate that yawing the rotor leads to a lateral shift in the wake and increased asymmetry, with a stronger shear layer forming on one side. This asymmetry promotes enhanced mixing between the wake and the surrounding flow, contributing to a faster downstream recovery of the velocity field. The proper orthogonal decomposition analysis shows that the most energetic modes are associated with large-scale wake deflection and meandering, while higher-order modes correspond to smaller and less stable flow structures within the shear layer. The temporal evolution of these modes illustrates how the wake responds to the yaw maneuver and gradually reaches a new quasi-steady state. Overall, the study provides insight into the influence of yaw on wind turbine wake dynamics and demonstrates the applicability of combining large-eddy simulation with proper orthogonal decomposition for wake analysis in offshore wind farm studies.

OceansVol. 7(2)
Jiangsu University (CN), Queensland University of Technology (AU)
Affordable and clean energy
Openalex Percentile: Top 29%
Wind Energy Research and Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research on Wake Characteristics of Dynamic Yawing Offshore Wind Turbine by Proper Orthogonal Decomposition — Longyan Wang, Bowen Zhang, et al. · Oceans (2026) | TGRS Research Map | TGRS