Articles | Volume 6, issue 5
https://doi.org/10.5194/wes-6-1247-2021
© Author(s) 2021. 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-6-1247-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Sep 2021
Research article |
| 17 Sep 2021
| 17 Sep 2021
FAST.Farm load validation for single wake situations at alpha ventus
Matthias Kretschmer
CORRESPONDING AUTHOR
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Jason Jonkman
National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401, USA
Vasilis Pettas
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
Po Wen Cheng
Stuttgart Wind Energy (SWE) at Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
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Vasilis Pettas, Matthias Kretschmer, Andrew Clifton, and Po Wen Cheng
Wind Energ. Sci., 6, 1455–1472, https://doi.org/10.5194/wes-6-1455-2021, https://doi.org/10.5194/wes-6-1455-2021, 2021
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This study aims to quantify the effect of inter-farm interactions based on long-term measurement data from the Alpha Ventus (AV) wind farm and the nearby FINO1 platform. AV was initially the only operating farm in the area, but in subsequent years several farms were built around it. This setup allows us to quantify the farm wake effects on the microclimate of AV and also on turbine loads and operational characteristics depending on the distance and size of the neighboring farms.
Moritz Gräfe, Vasilis Pettas, Nikolay Dimitrov, and Po Wen Cheng
Wind Energ. Sci., 9, 2175–2193, https://doi.org/10.5194/wes-9-2175-2024, https://doi.org/10.5194/wes-9-2175-2024, 2024
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This study explores a methodology using floater motion and nacelle-based lidar wind speed measurements to estimate the tension and damage equivalent loads (DELs) on floating offshore wind turbines' mooring lines. Results indicate that fairlead tension time series and DELs can be accurately estimated from floater motion time series. Using lidar measurements as model inputs for DEL predictions leads to similar accuracies as using displacement measurements of the floater.
Will Wiley, Jason Jonkman, and Amy Robertson
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-130, https://doi.org/10.5194/wes-2024-130, 2024
Preprint under review for WES
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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.
Lucas Carmo, Jason Jonkman, and Regis Thedin
Wind Energ. Sci., 9, 1827–1847, https://doi.org/10.5194/wes-9-1827-2024, https://doi.org/10.5194/wes-9-1827-2024, 2024
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As floating wind turbines progress to arrays with multiple units, it becomes important to understand how the wake of a floating turbine affects the performance of other units in the array. Due to the compliance of the floating substructure, the wake of a floating wind turbine may behave differently from that of a fixed turbine. In this work, we present an investigation of the mutual interaction between the motions of floating wind turbines and wakes.
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Wind Energ. Sci., 9, 1791–1810, https://doi.org/10.5194/wes-9-1791-2024, https://doi.org/10.5194/wes-9-1791-2024, 2024
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Wind Energ. Sci., 9, 1527–1545, https://doi.org/10.5194/wes-9-1527-2024, https://doi.org/10.5194/wes-9-1527-2024, 2024
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Kelsey Shaler, Eliot Quon, Hristo Ivanov, and Jason Jonkman
Wind Energ. Sci., 9, 1451–1463, https://doi.org/10.5194/wes-9-1451-2024, https://doi.org/10.5194/wes-9-1451-2024, 2024
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Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-44, https://doi.org/10.5194/wes-2024-44, 2024
Revised manuscript under review for WES
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The floating wind market is striving to scale up from a handful of prototypes to gigawatt-scale capacity, despite facing barriers of high costs in the deep-sea deployment. Shared mooring is promising in reducing material costs. This paper introduces a comprehensive design methodology for reliable shared mooring line configurations, and reveals their potential for cost-saving and power enhancement. These findings contribute to achieving cost-effective solutions for floating wind farms.
Francesco Papi, Jason Jonkman, Amy Robertson, and Alessandro Bianchini
Wind Energ. Sci., 9, 1069–1088, https://doi.org/10.5194/wes-9-1069-2024, https://doi.org/10.5194/wes-9-1069-2024, 2024
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Blade element momentum (BEM) theory is the backbone of many industry-standard aerodynamic models. However, the analysis of floating offshore wind turbines (FOWTs) introduces new challenges, which could put BEM models to the test. This study systematically compares four aerodynamic models, ranging from BEM to computational fluid dynamics, in an attempt to shed light on the unsteady aerodynamic phenomena that are at stake in FOWTs and whether BEM is able to model them appropriately.
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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.
Wei Yu, Sheng Tao Zhou, Frank Lemmer, and Po Wen Cheng
Wind Energ. Sci., 9, 1053–1068, https://doi.org/10.5194/wes-9-1053-2024, https://doi.org/10.5194/wes-9-1053-2024, 2024
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Integrating a tuned liquid multi-column damping (TLMCD) into a floating offshore wind turbine (FOWT) is challenging. The synergy between the TLMCD, the turbine controller, and substructure dynamics affects the FOWT's performance and cost. A control co-design optimization framework is developed to optimize the substructure, the TLMCD, and the blade pitch controller simultaneously. The results show that the optimization can significantly enhance FOWT system performance.
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Emmanuel Branlard, Jason Jonkman, Cameron Brown, and Jiatian Zhang
Wind Energ. Sci., 9, 1–24, https://doi.org/10.5194/wes-9-1-2024, https://doi.org/10.5194/wes-9-1-2024, 2024
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Wind Energ. Sci., 8, 1659–1691, https://doi.org/10.5194/wes-8-1659-2023, https://doi.org/10.5194/wes-8-1659-2023, 2023
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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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Wind Energ. Sci., 8, 1475–1493, https://doi.org/10.5194/wes-8-1475-2023, https://doi.org/10.5194/wes-8-1475-2023, 2023
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Wind turbines are designed to withstand any wind conditions they might encounter. This includes high-turbulence flow fields found within wind farms due to the presence of the wind turbines themselves. The international standard allows for two ways to account for wind farm turbulence in the design process. We compared both ways and found large differences between them. To avoid overdesign and enable a site-specific design, we suggest moving towards validated, higher-fidelity simulation tools.
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Wind Energ. Sci., 8, 925–946, https://doi.org/10.5194/wes-8-925-2023, https://doi.org/10.5194/wes-8-925-2023, 2023
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Roger Bergua, Amy Robertson, Jason Jonkman, Emmanuel Branlard, Alessandro Fontanella, Marco Belloli, Paolo Schito, Alberto Zasso, Giacomo Persico, Andrea Sanvito, Ervin Amet, Cédric Brun, Guillén Campaña-Alonso, Raquel Martín-San-Román, Ruolin Cai, Jifeng Cai, Quan Qian, Wen Maoshi, Alec Beardsell, Georg Pirrung, Néstor Ramos-García, Wei Shi, Jie Fu, Rémi Corniglion, Anaïs Lovera, Josean Galván, Tor Anders Nygaard, Carlos Renan dos Santos, Philippe Gilbert, Pierre-Antoine Joulin, Frédéric Blondel, Eelco Frickel, Peng Chen, Zhiqiang Hu, Ronan Boisard, Kutay Yilmazlar, Alessandro Croce, Violette Harnois, Lijun Zhang, Ye Li, Ander Aristondo, Iñigo Mendikoa Alonso, Simone Mancini, Koen Boorsma, Feike Savenije, David Marten, Rodrigo Soto-Valle, Christian W. Schulz, Stefan Netzband, Alessandro Bianchini, Francesco Papi, Stefano Cioni, Pau Trubat, Daniel Alarcon, Climent Molins, Marion Cormier, Konstantin Brüker, Thorsten Lutz, Qing Xiao, Zhongsheng Deng, Florence Haudin, and Akhilesh Goveas
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Koen Boorsma, Gerard Schepers, Helge Aagard Madsen, Georg Pirrung, Niels Sørensen, Galih Bangga, Manfred Imiela, Christian Grinderslev, Alexander Meyer Forsting, Wen Zhong Shen, Alessandro Croce, Stefano Cacciola, Alois Peter Schaffarczyk, Brandon Lobo, Frederic Blondel, Philippe Gilbert, Ronan Boisard, Leo Höning, Luca Greco, Claudio Testa, Emmanuel Branlard, Jason Jonkman, and Ganesh Vijayakumar
Wind Energ. Sci., 8, 211–230, https://doi.org/10.5194/wes-8-211-2023, https://doi.org/10.5194/wes-8-211-2023, 2023
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Within the framework of the fourth phase of the International Energy Agency's (IEA) Wind Task 29, a large comparison exercise between measurements and aeroelastic simulations has been carried out. Results were obtained from more than 19 simulation tools of various fidelity, originating from 12 institutes and compared to state-of-the-art field measurements. The result is a unique insight into the current status and accuracy of rotor aerodynamic modeling.
Feng Guo, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 8, 149–171, https://doi.org/10.5194/wes-8-149-2023, https://doi.org/10.5194/wes-8-149-2023, 2023
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The benefits of lidar-assisted control are evaluated using both the Mann model and Kaimal model-based 4D turbulence, considering the variation of turbulence parameters. Simulations are performed for the above-rated mean wind speed, using the NREL 5.0 MW reference wind turbine and a four-beam lidar system. Using lidar-assisted control reduces the variations in rotor speed, pitch rate, tower base fore–aft bending moment, and electrical power significantly.
Kelsey Shaler, Amy N. Robertson, and Jason Jonkman
Wind Energ. Sci., 8, 25–40, https://doi.org/10.5194/wes-8-25-2023, https://doi.org/10.5194/wes-8-25-2023, 2023
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This work evaluates which wind-inflow- and wake-related parameters have the greatest influence on fatigue and ultimate loads for turbines in a small wind farm. Twenty-eight parameters were screened using an elementary effects approach to identify the parameters that lead to the largest variation in these loads of each turbine. The findings show the increased importance of non-streamwise wind components and wake parameters in fatigue and ultimate load sensitivity of downstream turbines.
Konstanze Kölle, Tuhfe Göçmen, Irene Eguinoa, Leonardo Andrés Alcayaga Román, Maria Aparicio-Sanchez, Ju Feng, Johan Meyers, Vasilis Pettas, and Ishaan Sood
Wind Energ. Sci., 7, 2181–2200, https://doi.org/10.5194/wes-7-2181-2022, https://doi.org/10.5194/wes-7-2181-2022, 2022
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The paper studies wind farm flow control (WFFC) in simulations with variable electricity prices. The results indicate that considering the electricity price in the operational strategy can be beneficial with respect to the gained income compared to focusing on the power gain only. Moreover, revenue maximization by balancing power production and structural load reduction is demonstrated at the example of a single wind turbine.
Jason M. Jonkman, Emmanuel S. P. Branlard, and John P. Jasa
Wind Energ. Sci., 7, 559–571, https://doi.org/10.5194/wes-7-559-2022, https://doi.org/10.5194/wes-7-559-2022, 2022
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This paper summarizes efforts done to understand the impact of design parameter variations in the physical system (e.g., mass, stiffness, geometry, aerodynamic, and hydrodynamic coefficients) on the linearized system using OpenFAST in support of the development of the WEIS toolset to enable controls co-design of floating offshore wind turbines.
Yiyin Chen, Feng Guo, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 7, 539–558, https://doi.org/10.5194/wes-7-539-2022, https://doi.org/10.5194/wes-7-539-2022, 2022
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Lidar-assisted control of wind turbines requires a wind field generator capable of simulating wind evolution. Out of this need, we extend the Veers method for 3D wind field generation to 4D and propose a two-step Cholesky decomposition approach. Based on this, we develop a 4D wind field generator – evoTurb – coupled with TurbSim and Mann turbulence generator. We further investigate the impacts of the spatial discretization in 4D wind fields on lidar simulations to provide practical suggestions.
Emmanuel Branlard, Ian Brownstein, Benjamin Strom, Jason Jonkman, Scott Dana, and Edward Ian Baring-Gould
Wind Energ. Sci., 7, 455–467, https://doi.org/10.5194/wes-7-455-2022, https://doi.org/10.5194/wes-7-455-2022, 2022
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In this work, we present an aerodynamic tool that can model an arbitrary collections of wings, blades, rotors, and towers. With these functionalities, the tool can be used to study and design advanced wind energy concepts, such as horizontal-axis wind turbines, vertical-axis wind turbines, kites, or multi-rotors. This article describes the key features of the tool and presents multiple applications. Field measurements of horizontal- and vertical-axis wind turbines are used for comparison.
Vasilis Pettas, Matthias Kretschmer, Andrew Clifton, and Po Wen Cheng
Wind Energ. Sci., 6, 1455–1472, https://doi.org/10.5194/wes-6-1455-2021, https://doi.org/10.5194/wes-6-1455-2021, 2021
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This study aims to quantify the effect of inter-farm interactions based on long-term measurement data from the Alpha Ventus (AV) wind farm and the nearby FINO1 platform. AV was initially the only operating farm in the area, but in subsequent years several farms were built around it. This setup allows us to quantify the farm wake effects on the microclimate of AV and also on turbine loads and operational characteristics depending on the distance and size of the neighboring farms.
Davide Conti, Vasilis Pettas, Nikolay Dimitrov, and Alfredo Peña
Wind Energ. Sci., 6, 841–866, https://doi.org/10.5194/wes-6-841-2021, https://doi.org/10.5194/wes-6-841-2021, 2021
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We define two lidar-based procedures for improving the accuracy of wind turbine load assessment under wake conditions. The first approach incorporates lidar observations directly into turbulence fields serving as inputs for aeroelastic simulations; the second approach imposes lidar-fitted wake deficit time series on the turbulence fields. The uncertainty in the lidar-based power and load predictions is quantified for a variety of scanning configurations and atmosphere turbulence conditions.
Yiyin Chen, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 6, 61–91, https://doi.org/10.5194/wes-6-61-2021, https://doi.org/10.5194/wes-6-61-2021, 2021
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Wind evolution is currently of high interest, mainly due to the development of lidar-assisted wind turbine control (LAC). Moreover, 4D stochastic wind field simulations can be made possible by integrating wind evolution into 3D simulations to provide a more realistic simulation environment for LAC. Motivated by these factors, we investigate the potential of Gaussian process regression in the parameterization of a two-parameter wind evolution model using data of two nacelle-mounted lidars.
Martin Hofsäß, Dominique Bergmann, Jan Denzel, and Po Wen Cheng
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-81, https://doi.org/10.5194/wes-2019-81, 2019
Revised manuscript not accepted
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We needed a way to measure wind vectors and turbulence in complex, hard-to-access terrain. We equipped a model helicopter with a standard 3-D ultrasonic anemometer. Due to the hovering capabilities, stationary point measurements are possible. The first measurements were made in flat terrain. A 100 m high stationary wind measuring mast served as reference. The results were investigated in the time domain as well as in the frequency domain.
Steffen Raach, Bart Doekemeijer, Sjoerd Boersma, Jan-Willem van Wingerden, and Po Wen Cheng
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-54, https://doi.org/10.5194/wes-2019-54, 2019
Publication in WES not foreseen
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The presented work combines two control approaches of wake redirection control, feedforward wake redirection and feedback wake redirction. In our previous investigatins the lidar-assisted feedback control was studied and the advantages and disadvantages were discussed. The optimal yaw angles for the wind turbines are precomputed, the feedback takes care of uncertainties and disturbances. The concept is demonstrated in a high fidelity simulation model.
Amy N. Robertson, Kelsey Shaler, Latha Sethuraman, and Jason Jonkman
Wind Energ. Sci., 4, 479–513, https://doi.org/10.5194/wes-4-479-2019, https://doi.org/10.5194/wes-4-479-2019, 2019
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This paper identifies the most sensitive parameters for the load response of a 5 MW wind turbine. Two sets of parameters are examined: one set relating to the wind excitation characteristics and a second related to the physical properties of the wind turbine. The two sensitivity analyses are done separately, and the top most-sensitive parameters are identified for different load outputs throughout the structure. The findings will guide future validation campaigns and measurement needs.
Peter Graf, Katherine Dykes, Rick Damiani, Jason Jonkman, and Paul Veers
Wind Energ. Sci., 3, 475–487, https://doi.org/10.5194/wes-3-475-2018, https://doi.org/10.5194/wes-3-475-2018, 2018
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Current approaches to wind turbine extreme load estimation are insufficient to routinely and reliably make required estimates over 50-year return periods. Our work hybridizes the two main approaches and casts the problem as stochastic optimization. However, the extreme variability in turbine response implies even an optimal sampling strategy needs unrealistic computing resources. We therefore conclude that further improvement requires better understanding of the underlying causes of loads.
Kolja Müller and Po Wen Cheng
Wind Energ. Sci., 3, 149–162, https://doi.org/10.5194/wes-3-149-2018, https://doi.org/10.5194/wes-3-149-2018, 2018
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An efficient and accurate Monte Carlo approach is presented to assess the lifetime fatigue loading on a floating offshore wind turbine accurately. This is typically challenging in simulation effort due to the many different combinations of relevant environmental conditions which need to be considered. The applied method uses quasi-random Sobol sequences and shows promising performance with respect to convergence and accuracy.
Srinivas Guntur, Jason Jonkman, Ryan Sievers, Michael A. Sprague, Scott Schreck, and Qi Wang
Wind Energ. Sci., 2, 443–468, https://doi.org/10.5194/wes-2-443-2017, https://doi.org/10.5194/wes-2-443-2017, 2017
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This paper presents a validation and code-to-code verification of the U.S. Dept of Energy/NREL wind turbine aeroelastic code, FAST v8, on a 2.3 MW wind turbine. Model validation is critical to any model-based research and development activity, and validation efforts on large turbines, as the current one, are extremely rare, mainly due to the scale. This paper, which was a collaboration between NREL and Siemens Wind Power, successfully demonstrates and validates the capabilities of FAST.
Steffen Raach, David Schlipf, and Po Wen Cheng
Wind Energ. Sci., 2, 257–267, https://doi.org/10.5194/wes-2-257-2017, https://doi.org/10.5194/wes-2-257-2017, 2017
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This work provides a possible solution to closed-loop flow control in a wind farm.
The remote sensing technology, lidar, which is a laser-based measurement system, is used to obtain wind speed information behind a wind turbine. The measurements are processed using a model-based approach to estimate position information of the wake. The information is then used in a controller to redirect the wake to the desired position. Altogether, the concept aims to increase the power output of a wind farm.
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Brief communication: Structural monitoring for lifetime extension of offshore wind monopiles: can strain measurements at one level tell us everything?
Simulation of an offshore wind farm using fluid power for centralized electricity generation
Effect of foundation modelling on the fatigue lifetime of a monopile-based offshore wind turbine
Juan-Andrés Pérez-Rúa and Nicolaos Antonio Cutululis
Wind Energ. Sci., 7, 925–942, https://doi.org/10.5194/wes-7-925-2022, https://doi.org/10.5194/wes-7-925-2022, 2022
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Wind farms are becoming larger, and they are shaping up as one of the main drivers towards full green energy transition. Because of their massive proliferation, more and more attention is nowadays focused on optimal design of these power plants. We propose an optimization framework in order to contribute to further cost reductions, by simultaneously designing the wind turbines and cable layout. We show the capability of the framework to improve designs compared to the classic approach.
Andreas Rott, Jörge Schneemann, Frauke Theuer, Juan José Trujillo Quintero, and Martin Kühn
Wind Energ. Sci., 7, 283–297, https://doi.org/10.5194/wes-7-283-2022, https://doi.org/10.5194/wes-7-283-2022, 2022
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We present three methods that can determine the alignment of a lidar placed on the transition piece of an offshore wind turbine based on measurements with the instrument: a practical implementation of hard targeting for north alignment, a method called sea surface levelling to determine the levelling of the system from water surface measurements, and a model that can determine the dynamic levelling based on the operating status of the wind turbine.
Aemilius A. W. van Vondelen, Sachin T. Navalkar, Alexandros Iliopoulos, Daan C. van der Hoek, and Jan-Willem van Wingerden
Wind Energ. Sci., 7, 161–184, https://doi.org/10.5194/wes-7-161-2022, https://doi.org/10.5194/wes-7-161-2022, 2022
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The damping of an offshore wind turbine is a difficult physical quantity to predict, although it plays a major role in a cost-effective turbine design. This paper presents a review of all approaches that can be used for damping estimation directly from operational wind turbine data. As each use case is different, a novel suitability table is presented to enable the user to choose the most appropriate approach for the given availability and characteristics of measurement data.
Aurélien Babarit, Félix Gorintin, Pierrick de Belizal, Antoine Neau, Giovanni Bordogna, and Jean-Christophe Gilloteaux
Wind Energ. Sci., 6, 1191–1204, https://doi.org/10.5194/wes-6-1191-2021, https://doi.org/10.5194/wes-6-1191-2021, 2021
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In this paper, a new energy system for the conversion of far-offshore wind energy into methanol is proposed, and the cost of energy is estimated. Results show that this system could produce approximately 70 000 t of methanol per annum at a cost comparable to that of methanol produced by offshore wind farms in the long term.
Romanas Puisa, Victor Bolbot, Andrew Newman, and Dracos Vassalos
Wind Energ. Sci., 6, 273–286, https://doi.org/10.5194/wes-6-273-2021, https://doi.org/10.5194/wes-6-273-2021, 2021
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The paper proposes a quantitative, non-probabilistic metric for the preliminary comparison of safety of windfarm service operation vessels (SOV) in typical phases of operation. The metric is used as a conditional proxy for the incident likelihood, conditioned upon the presence of similar resources (manpower, time, skills, knowledge, information, etc.) for risk management across compared operational phases.
Simone Mancini, Koen Boorsma, Marco Caboni, Marion Cormier, Thorsten Lutz, Paolo Schito, and Alberto Zasso
Wind Energ. Sci., 5, 1713–1730, https://doi.org/10.5194/wes-5-1713-2020, https://doi.org/10.5194/wes-5-1713-2020, 2020
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This work characterizes the unsteady aerodynamic response of a scaled version of a 10 MW floating wind turbine subjected to an imposed platform motion. The focus has been put on the simple yet significant motion along the wind's direction (surge). For this purpose, different state-of-the-art aerodynamic codes have been used, validating the outcomes with detailed wind tunnel experiments. This paper sheds light on floating-turbine unsteady aerodynamics for a more conscious controller design.
Robbie Herring, Kirsten Dyer, Paul Howkins, and Carwyn Ward
Wind Energ. Sci., 5, 1399–1409, https://doi.org/10.5194/wes-5-1399-2020, https://doi.org/10.5194/wes-5-1399-2020, 2020
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Leading edge erosion has developed into a significant problem for the offshore wind industry. It is important to understand the offshore precipitation environment to model and predict the onset of erosion and to design systems to protect against it. In this study, the offshore environment was characterised using up-to-date measuring techniques. A general offshore droplet size distribution that can be used to improve lifetime prediction techniques has been presented.
Tobias Ahsbahs, Galen Maclaurin, Caroline Draxl, Christopher R. Jackson, Frank Monaldo, and Merete Badger
Wind Energ. Sci., 5, 1191–1210, https://doi.org/10.5194/wes-5-1191-2020, https://doi.org/10.5194/wes-5-1191-2020, 2020
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Before constructing wind farms we need to know how much energy they will produce. This requires knowledge of long-term wind conditions from either measurements or models. At the US East Coast there are few wind measurements and little experience with offshore wind farms. Therefore, we created a satellite-based high-resolution wind resource map to quantify spatial variations in the wind conditions over potential sites for wind farms and found larger variation than modelling suggested.
Anna-Maria Tilg, Charlotte Bay Hasager, Hans-Jürgen Kirtzel, and Poul Hummelshøj
Wind Energ. Sci., 5, 977–981, https://doi.org/10.5194/wes-5-977-2020, https://doi.org/10.5194/wes-5-977-2020, 2020
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Recently, there has been an increased awareness of leading-edge erosion of wind turbine blades. An option to mitigate the erosion at the leading edges is the deceleration of the wind turbine blades during severe precipitation events. This work shows that a vertically pointing radar can be used to nowcast precipitation events with the required spatial and temporal resolution. Furthermore, nowcasting allows a reduction in the rotational speed prior to the impact of precipitation on the blades.
Aurélien Babarit, Gaël Clodic, Simon Delvoye, and Jean-Christophe Gilloteaux
Wind Energ. Sci., 5, 839–853, https://doi.org/10.5194/wes-5-839-2020, https://doi.org/10.5194/wes-5-839-2020, 2020
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This paper addresses the topic of far-offshore wind energy exploitation. Far-offshore wind energy exploitation is not feasible with grid-connected floating wind turbines because grid-connection cost, installation cost and O&M cost would be prohibitive. An enabling technology is the energy ship concept, which is described and modeled in the paper. A design of an energy ship is proposed. It is estimated that it could produce 5 GWh per annum of chemical energy (methanol).
Michael Denis Mifsud, Tonio Sant, and Robert Nicholas Farrugia
Wind Energ. Sci., 5, 601–621, https://doi.org/10.5194/wes-5-601-2020, https://doi.org/10.5194/wes-5-601-2020, 2020
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In offshore wind, it is important to have an accurate wind resource assessment. Measure–correlate–predict (MCP) is a statistical method used in the assessment of the wind resource at a candidate site. Being a statistical method, it is subject to uncertainty, resulting in an uncertainty in the power output from the wind farm. This study involves the use of wind data from the island of Malta and uses a hypothetical wind farm to establish the best MCP methodology for the wind resource assessment.
Aurélien Babarit, Simon Delvoye, Gaël Clodic, and Jean-Christophe Gilloteaux
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-101, https://doi.org/10.5194/wes-2019-101, 2020
Revised manuscript not accepted
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This paper addresses the topic of far-offshore wind energy exploitation. Far-offshore wind energy exploitation is not feasible with current technology because grid-connection cost, installation cost and O&M cost would be prohibitive. An enabling technology for far-offshore wind energy is the energy ship concept, which has been described, modelled and analyzed in a companion paper. This paper provides a cost model and cost estimates for an energy system based on the energy ship concept.
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.
Jakob Ilsted Bech, Charlotte Bay Hasager, and Christian Bak
Wind Energ. Sci., 3, 729–748, https://doi.org/10.5194/wes-3-729-2018, https://doi.org/10.5194/wes-3-729-2018, 2018
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Rain erosion on wind turbine blades is a severe challenge for wind energy today. It causes significant losses in power production, and large sums are spent on inspection and repair.
Blade life can be extended, power production increased and maintenance costs reduced by rotor speed reduction at extreme precipitation events. Combining erosion test results, meteorological data and models of blade performance, we show that a turbine control strategy is a promising new weapon against blade erosion.
Tobias Ahsbahs, Merete Badger, Patrick Volker, Kurt S. Hansen, and Charlotte B. Hasager
Wind Energ. Sci., 3, 573–588, https://doi.org/10.5194/wes-3-573-2018, https://doi.org/10.5194/wes-3-573-2018, 2018
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Satellites offer wind measurements offshore and can resolve the wind speed on scales of up to 500 m. To date, this data is not routinely used in the industry for planning wind farms. We show that this data can be used to predict local differences in the mean wind speed around the Anholt offshore wind farm. With satellite data, site-specific wind measurements can be introduced early in the planning phase of an offshore wind farm and help decision makers.
Sebastian Schafhirt and Michael Muskulus
Wind Energ. Sci., 3, 25–41, https://doi.org/10.5194/wes-3-25-2018, https://doi.org/10.5194/wes-3-25-2018, 2018
Lisa Ziegler, Ursula Smolka, Nicolai Cosack, and Michael Muskulus
Wind Energ. Sci., 2, 469–476, https://doi.org/10.5194/wes-2-469-2017, https://doi.org/10.5194/wes-2-469-2017, 2017
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The first larger offshore wind farms are reaching a mature age. Operators have to take actions for monitoring now in order to have accurate knowledge on structural reserves later. This knowledge is important to make decisions on lifetime extension. Many offshore wind turbines have one set of strain gauges already installed at the transition piece. We present a simple and robust method to extrapolate these measurements to other locations of the monopile without need of additional instrumentation.
Antonio Jarquin Laguna
Wind Energ. Sci., 2, 387–402, https://doi.org/10.5194/wes-2-387-2017, https://doi.org/10.5194/wes-2-387-2017, 2017
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This paper presents the idea of centralized electricity production in a wind farm by means of water technology. A new way of generating and transmitting wind energy is explored with no intermediate electrical conversion until the energy has reached the central offshore platform. This work includes the modelling and simulations of a hypothetical hydraulic wind farm, where results indicate good performance despite the turbulent wind conditions and wake effects.
Steffen Aasen, Ana M. Page, Kristoffer Skjolden Skau, and Tor Anders Nygaard
Wind Energ. Sci., 2, 361–376, https://doi.org/10.5194/wes-2-361-2017, https://doi.org/10.5194/wes-2-361-2017, 2017
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The industry standard for analysis of monopile foundations is inaccurate, and alternative models for foundation behavior are needed. This study investigates how four different soil-foundation models affect the fatigue damage of an offshore wind turbine with a monopile foundation. Stiffness and damping properties have a noticeable effect, in particular for idling cases. At mud-line, accumulated fatigue damage varied up to 22 % depending on the foundation model used.
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Short summary
We perform a validation of the new simulation tool FAST.Farm for the prediction of power output and structural loads in single wake conditions with respect to measurement data from the offshore wind farm alpha ventus. With a new wake-added turbulence functionality added to FAST.Farm, good agreement between simulations and measurements is achieved for the considered quantities. We hereby give insights into load characteristics of an offshore wind turbine subjected to single wake conditions.
We perform a validation of the new simulation tool FAST.Farm for the prediction of power output...
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