Articles | Volume 8, issue 12
https://doi.org/10.5194/wes-8-1873-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-8-1873-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new methodology for upscaling semi-submersible platforms for floating offshore wind turbines
Kaylie L. Roach
Mechanical Engineering, University of Massachusetts Amherst, Amherst, MA, 01003, USA
Matthew A. Lackner
CORRESPONDING AUTHOR
Mechanical Engineering, University of Massachusetts Amherst, Amherst, MA, 01003, USA
James F. Manwell
Mechanical Engineering, University of Massachusetts Amherst, Amherst, MA, 01003, USA
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Paul Veers, Carlo L. Bottasso, Lance Manuel, Jonathan Naughton, Lucy Pao, Joshua Paquette, Amy Robertson, Michael Robinson, Shreyas Ananthan, Thanasis Barlas, Alessandro Bianchini, Henrik Bredmose, Sergio González Horcas, Jonathan Keller, Helge Aagaard Madsen, James Manwell, Patrick Moriarty, Stephen Nolet, and Jennifer Rinker
Wind Energ. Sci., 8, 1071–1131, https://doi.org/10.5194/wes-8-1071-2023, https://doi.org/10.5194/wes-8-1071-2023, 2023
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Critical unknowns in the design, manufacturing, and operation of future wind turbine and wind plant systems are articulated, and key research activities are recommended.
Maciej M. Mroczek, Sanjay Raja Arwade, and Matthew A. Lackner
Wind Energ. Sci., 8, 807–817, https://doi.org/10.5194/wes-8-807-2023, https://doi.org/10.5194/wes-8-807-2023, 2023
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Benefits of orientating a three-legged offshore wind jacket relative to the metocean conditions for pile design are assessed considering the International Energy Agency 15 MW reference turbine and a reference site off the coast of Massachusetts. Results, based on the considered conditions, show that the pile design can be optimized by orientating the jacket relative to the dominant wave direction. This design optimization can be used on offshore wind projects to provide cost and risk reductions.
Amber Kapoor, Slimane Ouakka, Sanjay R. Arwade, Julie K. Lundquist, Matthew A. Lackner, Andrew T. Myers, Rochelle P. Worsnop, and George H. Bryan
Wind Energ. Sci., 5, 89–104, https://doi.org/10.5194/wes-5-89-2020, https://doi.org/10.5194/wes-5-89-2020, 2020
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Offshore wind energy is a burgeoning area of renewable energy that is at an early stage of development in the United States. Exposure of offshore wind turbines to hurricanes must be assessed and mitigated to ensure the security of the renewable energy supply. This research assesses the impact of hurricane wind fields on the structural response of wind turbines. Such wind fields have characteristics that may pose heretofore unforeseen structural challenges to offshore wind turbines.
Related subject area
Thematic area: Wind technologies | Topic: Offshore technology
Effect of rotor induction and peak shaving on energy performance and cost of stationary unmoored floating offshore wind turbines
Experimental validation of parked loads for a floating vertical axis wind turbine: wind–wave basin tests
Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data
Estimating microplastic emissions from offshore wind turbine blades in the Dutch North Sea
A new gridded offshore wind profile product for US coasts using machine learning and satellite observations
Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads in extreme idling conditions
Gaussian mixture autoencoder for uncertainty-aware damage identification in a floating offshore wind turbine
Comparative anomaly detection for floating offshore wind turbines using in-situ data
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Dynamic performance of a passively self-adjusting floating wind farm layout to increase the annual energy production
OC6 project Phase IV: validation of numerical models for novel floating offshore wind support structures
Quantifying the impact of modeling fidelity on different substructure concepts for floating offshore wind turbines – Part 1: Validation of the hydrodynamic module QBlade-Ocean
Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads
Design optimization of offshore wind jacket piles by assessing support structure orientation relative to metocean conditions
Comparison of optimal power production and operation of unmoored floating offshore wind turbines and energy ships
Aurélien Babarit, Maximilien André, and Vincent Leroy
Wind Energ. Sci., 10, 1439–1449, https://doi.org/10.5194/wes-10-1439-2025, https://doi.org/10.5194/wes-10-1439-2025, 2025
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This study deals with energy performance optimization of unmoored floating offshore wind turbines (UFOWTs). UFOWTs use thrusters in lieu of mooring systems for position control. Previous studies have shown that net positive power generation can be achieved depending on design. In this study, we investigate the effect of rotor induction and peak shaving.
Md. Sanower Hossain and D. Todd Griffith
Wind Energ. Sci., 10, 1211–1230, https://doi.org/10.5194/wes-10-1211-2025, https://doi.org/10.5194/wes-10-1211-2025, 2025
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The document presents an experimental study on the parked loads of floating vertical axis wind turbines (VAWTs) in a wind and wave basin, focusing on the effects of wind speed, solidity, and floating platform dynamics. Findings show that higher wind speed and higher solidity generally increase the parked loads, while a floating platform introduces additional effects due to tilting. A semi-numerical model was also presented to predict the parked loads, which helps enhance VAWT design.
Simon Daenens, Timothy Verstraeten, Pieter-Jan Daems, Ann Nowé, and Jan Helsen
Wind Energ. Sci., 10, 1137–1152, https://doi.org/10.5194/wes-10-1137-2025, https://doi.org/10.5194/wes-10-1137-2025, 2025
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This study presents a novel model for predicting wind turbine power output at a high temporal resolution in wind farms using a hybrid graph neural network (GNN) and long short-term memory (LSTM) architecture. By modeling the wind farm as a graph, the model captures both spatial and temporal dynamics, outperforming traditional power curve methods. Integrated with a normal behavior model (NBM) framework, the model effectively identifies and analyzes power loss events.
Marco Caboni, Anna Elisa Schwarz, Henk Slot, and Harald van der Mijle Meijer
Wind Energ. Sci., 10, 1123–1136, https://doi.org/10.5194/wes-10-1123-2025, https://doi.org/10.5194/wes-10-1123-2025, 2025
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In this study, we assessed the total quantity of microplastics emitted by wind turbines currently operating in the Dutch North Sea. The estimates of microplastics currently emitted from offshore wind turbines in the Netherlands account for a very small portion of the total microplastics released offshore in the Netherlands, specifically less than 1 ‰.
James Frech, Korak Saha, Paige D. Lavin, Huai-Min Zhang, James Reagan, and Brandon Fung
Wind Energ. Sci., 10, 1077–1099, https://doi.org/10.5194/wes-10-1077-2025, https://doi.org/10.5194/wes-10-1077-2025, 2025
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A machine learning model is developed using lidar stations around US coasts to extrapolate wind speed profiles up to the hub heights of wind turbines from surface wind speeds. Independent validation shows that our model vastly outperforms traditional methods for vertical wind extrapolation. We produce a new long-term gridded dataset of wind speed profiles from 20 to 200 m at 0.25° and 6-hourly resolution from 1987 to the present by applying this model to the National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Information (NCEI) Blended Seawinds product.
Will Wiley, Jason Jonkman, and Amy Robertson
Wind Energ. Sci., 10, 941–970, https://doi.org/10.5194/wes-10-941-2025, https://doi.org/10.5194/wes-10-941-2025, 2025
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Numerical models, used to assess loads on floating offshore wind turbines, require many input parameters to describe air and water conditions, system properties, and load calculations. All parameters have some possible range, due to uncertainty and/or variations with time. The selected values can have important effects on the uncertainty in the resulting loads. This work identifies the input parameters that have the most impact on ultimate and fatigue loads for extreme storm load cases.
Ana Fernandez-Navamuel, Nicolas Gorostidi, David Pardo, Vincenzo Nava, and Eleni Chatzi
Wind Energ. Sci., 10, 857–885, https://doi.org/10.5194/wes-10-857-2025, https://doi.org/10.5194/wes-10-857-2025, 2025
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This work employs deep neural networks to identify damage in the mooring system of a floating offshore wind turbine using measurements from the platform response. We account for the effect of uncertainty caused by the existence of multiple solutions using a Gaussian mixture model to describe the damage condition estimates. The results reveal the capability of the methodology to discover the uncertainty in the assessment, which increases as the instrumentation system becomes more limited.
Adrien Hirvoas, César Aguilera, Matthieu Perrault, Damien Desbordes, and Romain Ribault
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-189, https://doi.org/10.5194/wes-2024-189, 2025
Revised manuscript accepted for WES
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This study compares two methods for detecting downtime in the Zefyros floating offshore wind turbine off Norway's coast. The first method uses kurtosis to find signal anomalies, while the second employs a deep learning auto-encoder to reduce and reconstruct data, identifying irregularities. Using one month of sensor data, the study finds the deep learning method more accurate than kurtosis. This research advances the use of deep learning for effective wind turbine monitoring.
Marco Caboni and Gerwin van Dalum
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-174, https://doi.org/10.5194/wes-2024-174, 2024
Revised manuscript accepted for WES
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Weather simulations carried out over a decade showed that the average erosivity of rainfall on wind turbine blades increases from the southwestern part of the Dutch North Sea to the northeastern region. These results suggest that future wind farms developed in the northeast are likely to encounter higher erosion rates compared to those currently operating in the southwest. This requires special attention when developing mitigation strategies.
Mohammad Youssef Mahfouz, Ericka Lozon, Matthew Hall, and Po Wen Cheng
Wind Energ. Sci., 9, 1595–1615, https://doi.org/10.5194/wes-9-1595-2024, https://doi.org/10.5194/wes-9-1595-2024, 2024
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As climate change increasingly impacts our daily lives, a transition towards cleaner energy is needed. With all the growth in floating offshore wind and the planned floating wind farms (FWFs) in the next few years, we urgently need new techniques and methodologies to accommodate the differences between the fixed bottom and FWFs. This paper presents a novel methodology to decrease aerodynamic losses inside an FWF by passively relocating the downwind floating wind turbines out of the wakes.
Roger Bergua, Will Wiley, Amy Robertson, Jason Jonkman, Cédric Brun, Jean-Philippe Pineau, Quan Qian, Wen Maoshi, Alec Beardsell, Joshua Cutler, Fabio Pierella, Christian Anker Hansen, Wei Shi, Jie Fu, Lehan Hu, Prokopios Vlachogiannis, Christophe Peyrard, Christopher Simon Wright, Dallán Friel, Øyvind Waage Hanssen-Bauer, Carlos Renan dos Santos, Eelco Frickel, Hafizul Islam, Arjen Koop, Zhiqiang Hu, Jihuai Yang, Tristan Quideau, Violette Harnois, Kelsey Shaler, Stefan Netzband, Daniel Alarcón, Pau Trubat, Aengus Connolly, Seán B. Leen, and Oisín Conway
Wind Energ. Sci., 9, 1025–1051, https://doi.org/10.5194/wes-9-1025-2024, https://doi.org/10.5194/wes-9-1025-2024, 2024
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This paper provides a comparison for a floating offshore wind turbine between the motion and loading estimated by numerical models and measurements. The floating support structure is a novel design that includes a counterweight to provide floating stability to the system. The comparison between numerical models and the measurements includes system motion, tower loads, mooring line loads, and loading within the floating support structure.
Robert Behrens de Luna, Sebastian Perez-Becker, Joseph Saverin, David Marten, Francesco Papi, Marie-Laure Ducasse, Félicien Bonnefoy, Alessandro Bianchini, and Christian-Oliver Paschereit
Wind Energ. Sci., 9, 623–649, https://doi.org/10.5194/wes-9-623-2024, https://doi.org/10.5194/wes-9-623-2024, 2024
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A novel hydrodynamic module of QBlade is validated on three floating offshore wind turbine concepts with experiments and two widely used simulation tools. Further, a recently proposed method to enhance the prediction of slowly varying drift forces is adopted and tested in varying met-ocean conditions. The hydrodynamic capability of QBlade matches the current state of the art and demonstrates significant improvement regarding the prediction of slowly varying drift forces with the enhanced model.
Will Wiley, Jason Jonkman, Amy Robertson, and Kelsey Shaler
Wind Energ. Sci., 8, 1575–1595, https://doi.org/10.5194/wes-8-1575-2023, https://doi.org/10.5194/wes-8-1575-2023, 2023
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A sensitivity analysis determined the modeling parameters for an operating floating offshore wind turbine with the biggest impact on the ultimate and fatigue loads. The loads were the most sensitive to the standard deviation of the wind speed. Ultimate and fatigue mooring loads were highly sensitive to the current speed; only the fatigue mooring loads were sensitive to wave parameters. The largest platform rotation was the most sensitive to the platform horizontal center of gravity.
Maciej M. Mroczek, Sanjay Raja Arwade, and Matthew A. Lackner
Wind Energ. Sci., 8, 807–817, https://doi.org/10.5194/wes-8-807-2023, https://doi.org/10.5194/wes-8-807-2023, 2023
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Benefits of orientating a three-legged offshore wind jacket relative to the metocean conditions for pile design are assessed considering the International Energy Agency 15 MW reference turbine and a reference site off the coast of Massachusetts. Results, based on the considered conditions, show that the pile design can be optimized by orientating the jacket relative to the dominant wave direction. This design optimization can be used on offshore wind projects to provide cost and risk reductions.
Patrick Connolly and Curran Crawford
Wind Energ. Sci., 8, 725–746, https://doi.org/10.5194/wes-8-725-2023, https://doi.org/10.5194/wes-8-725-2023, 2023
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Mobile offshore wind energy systems are a potential way of producing green fuels from the untapped wind resource that lies far offshore. Herein, computational models of two such systems were developed and verified. The models are able to predict the power output of each system based on wind condition inputs. Results show that both systems have merits and that, contrary to existing results, unmoored floating wind turbines may produce as much power as fixed ones, given the right conditions.
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This paper presents an upscaling methodology for floating offshore wind turbine platforms using two case studies. The offshore wind turbine industry is trending towards fewer, larger offshore wind turbines within a farm, which is motivated by the per unit cost of a wind farm (including installation, interconnection, and maintenance costs). The results show the platform steel mass to be favorable with upscaling.
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