Articles | Volume 9, issue 2
https://doi.org/10.5194/wes-9-359-2024
© Author(s) 2024. 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-9-359-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Feb 2024
Research article |
| 15 Feb 2024
| 15 Feb 2024
Hybrid-Lambda: a low-specific-rating rotor concept for offshore wind turbines
Carl von Ossietzky Universität Oldenburg, Institute of Physics, ForWind – Center for Wind Energy Research, Küpkersweg 70, 26129 Oldenburg, Germany
Frederik Berger
Carl von Ossietzky Universität Oldenburg, Institute of Physics, ForWind – Center for Wind Energy Research, Küpkersweg 70, 26129 Oldenburg, Germany
Vlaho Petrović
Carl von Ossietzky Universität Oldenburg, Institute of Physics, ForWind – Center for Wind Energy Research, Küpkersweg 70, 26129 Oldenburg, Germany
Martin Kühn
Carl von Ossietzky Universität Oldenburg, Institute of Physics, ForWind – Center for Wind Energy Research, Küpkersweg 70, 26129 Oldenburg, Germany
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Jörge Schneemann, Andreas Rott, Martin Dörenkämper, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 5, 29–49, https://doi.org/10.5194/wes-5-29-2020, https://doi.org/10.5194/wes-5-29-2020, 2020
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Offshore wind farm clusters cause reduced wind speeds in downstream regions which can extend over more than 50 km.
We analysed the impact of these so-called cluster wakes on a distant wind farm using remote-sensing wind measurements and power production data.
Cluster wakes caused power losses up to 55 km downstream in certain atmospheric states.
A better understanding of cluster wake effects reduces uncertainties in offshore wind resource assessment and improves offshore areal planning.
Róbert Ungurán, Vlaho Petrović, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 677–692, https://doi.org/10.5194/wes-4-677-2019, https://doi.org/10.5194/wes-4-677-2019, 2019
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A novel lidar-based sensory system for wind turbine control is proposed. The main contributions are the parametrization method of the novel measurement system, the identification of possible sources of measurement uncertainty, and their modelling. Although not the focus of the submitted paper, the mentioned contributions represent essential building blocks for robust feedback–feedforward wind turbine control development which could be used to improve wind turbine control strategies.
Mehdi Vali, Vlaho Petrović, Gerald Steinfeld, Lucy Y. Pao, and Martin Kühn
Wind Energ. Sci., 4, 139–161, https://doi.org/10.5194/wes-4-139-2019, https://doi.org/10.5194/wes-4-139-2019, 2019
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Andreas Rott, Bart Doekemeijer, Janna Kristina Seifert, Jan-Willem van Wingerden, and Martin Kühn
Wind Energ. Sci., 3, 869–882, https://doi.org/10.5194/wes-3-869-2018, https://doi.org/10.5194/wes-3-869-2018, 2018
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Niko Mittelmeier and Martin Kühn
Wind Energ. Sci., 3, 395–408, https://doi.org/10.5194/wes-3-395-2018, https://doi.org/10.5194/wes-3-395-2018, 2018
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Laura Valldecabres, Alfredo Peña, Michael Courtney, Lueder von Bremen, and Martin Kühn
Wind Energ. Sci., 3, 313–327, https://doi.org/10.5194/wes-3-313-2018, https://doi.org/10.5194/wes-3-313-2018, 2018
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This paper focuses on the use of scanning lidars for very short-term forecasting of wind speeds in a near-coastal area. An extensive data set of offshore lidar measurements up to 6 km has been used for this purpose. Using dual-doppler measurements, the topographic characteristics of the area have been modelled. Assuming Taylor's frozen turbulence and applying the topographic corrections, we demonstrate that we can forecast wind speeds with more accuracy than the benchmarks persistence or ARIMA.
Lukas Vollmer, Gerald Steinfeld, and Martin Kühn
Wind Energ. Sci., 2, 603–614, https://doi.org/10.5194/wes-2-603-2017, https://doi.org/10.5194/wes-2-603-2017, 2017
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Davide Trabucchi, Lukas Vollmer, and Martin Kühn
Wind Energ. Sci., 2, 569–586, https://doi.org/10.5194/wes-2-569-2017, https://doi.org/10.5194/wes-2-569-2017, 2017
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The wakes of wind turbines cause losses in the energy production of a wind farm. The accuracy of models applied to predict wake losses is a key factor for new wind projects. This paper presents an engineering wake model that can simulate merging wakes on the basis of physical principles. We used high-fidelity simulations of merging wakes to assess this model and found a better agreement with the reference than commonly used models implementing the superposition of individual wakes.
Niko Mittelmeier, Julian Allin, Tomas Blodau, Davide Trabucchi, Gerald Steinfeld, Andreas Rott, and Martin Kühn
Wind Energ. Sci., 2, 477–490, https://doi.org/10.5194/wes-2-477-2017, https://doi.org/10.5194/wes-2-477-2017, 2017
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Stability classification is usually based on measurements from met masts, buoys or lidars. The objective of this paper is to find a classification for stability based on wind turbine supervisory control and data acquisition measurements in order to fit engineering wake models better to the current ambient conditions. The proposed signal is very sensitive to increased turbulence. It allows us to distinguish between conditions with different magnitudes of wake effects.
Marijn Floris van Dooren, Filippo Campagnolo, Mikael Sjöholm, Nikolas Angelou, Torben Mikkelsen, and Martin Kühn
Wind Energ. Sci., 2, 329–341, https://doi.org/10.5194/wes-2-329-2017, https://doi.org/10.5194/wes-2-329-2017, 2017
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We conducted measurements in a wind tunnel with the remote sensing technique lidar to map the flow around a row of three model wind turbines. Two lidars were positioned near the wind tunnel walls to measure the two-dimensional wind vector over a defined scanning line or area without influencing the flow itself. A comparison of the lidar measurements with a hot-wire probe and a thorough uncertainty analysis confirmed the usefulness of lidar technology for such flow measurements in a wind tunnel.
Niko Mittelmeier, Tomas Blodau, and Martin Kühn
Wind Energ. Sci., 2, 175–187, https://doi.org/10.5194/wes-2-175-2017, https://doi.org/10.5194/wes-2-175-2017, 2017
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Efficient detection of wind turbines operating below their expected power output and immediate corrections help maximize asset value. The method presented estimates the environmental conditions from turbine states and uses pre-calculated power lookup tables from a numeric wake model to predict the expected power output. Deviations between the expected and the measured power output are an indication of underperformance. A demonstration of the method's ability to detect underperformance is given.
Lukas Vollmer, Gerald Steinfeld, Detlev Heinemann, and Martin Kühn
Wind Energ. Sci., 1, 129–141, https://doi.org/10.5194/wes-1-129-2016, https://doi.org/10.5194/wes-1-129-2016, 2016
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The wake flow downstream of yaw misaligned wind turbines is studied in numeric simulations of different atmospheric turbulence and shear conditions. We find that the average trajectory of the wake as well as the variation about this average is influenced by the thermal stability of the atmosphere. The results suggest that an intentional intervention in the yaw control of individual turbines to increase overall wind farm performance might be not successful during unstable thermal conditions.
Juan José Trujillo, Janna Kristina Seifert, Ines Würth, David Schlipf, and Martin Kühn
Wind Energ. Sci., 1, 41–53, https://doi.org/10.5194/wes-1-41-2016, https://doi.org/10.5194/wes-1-41-2016, 2016
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We present the analysis of the trajectories followed by the wind, in the immediate vicinity, behind an offshore wind turbine and their dependence on its yaw misalignment. We apply wake tracking on wind fields measured with a lidar (light detection and ranging) system located at the nacelle of the wind turbine and pointing downstream. The analysis reveals discrepancies of the estimated mean wake paths against theoretical and wind tunnel experiments using different wake-tracking techniques.
Related subject area
Thematic area: Wind technologies | Topic: Design concepts and methods for plants, turbines, and components
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Wind Energ. Sci., 10, 461–481, https://doi.org/10.5194/wes-10-461-2025, https://doi.org/10.5194/wes-10-461-2025, 2025
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Wind Energ. Sci., 10, 401–415, https://doi.org/10.5194/wes-10-401-2025, https://doi.org/10.5194/wes-10-401-2025, 2025
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A methodology for evaluating fretting in wind turbine pitch bearing raceways is presented, and a case study is evaluated. The methodology considers the coupled effects of radial fretting and rotational fretting. As result, critical locations based on the dissipated energy are identified for the different wind speeds and the contributions of operational and non-operational times, as well as the prediction of damage shapes on the raceway for both cases, are evaluated independently and compared.
Laurence Morgan, Abbas Kazemi Amiri, William Leithead, and James Carroll
Wind Energ. Sci., 10, 381–399, https://doi.org/10.5194/wes-10-381-2025, https://doi.org/10.5194/wes-10-381-2025, 2025
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This paper presents a systematic study of the effect of blade inclination angle, chord distribution, and blade length on vertical-axis wind turbine performance. It shows that, for rotors of identical power production, both blade volume and rotor torque can be significantly reduced through the use of aerodynamically optimised inclined rotor blades. This demonstrates the potential of vertical rotors to reduce the cost of energy for offshore wind when compared to horizontal rotors.
Tahir H. Malik and Christian Bak
Wind Energ. Sci., 10, 269–291, https://doi.org/10.5194/wes-10-269-2025, https://doi.org/10.5194/wes-10-269-2025, 2025
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This research integrates custom sensors into wind turbine simulation models for improved performance monitoring utilising a turbine performance integral (TPI) method developed here. Real-world data validation demonstrates that appropriate sensor selection improves wind turbine performance monitoring. This approach addresses the need for precise performance assessments in the evolving wind energy sector, ultimately promoting sustainability and efficiency.
Tahir H. Malik and Christian Bak
Wind Energ. Sci., 10, 227–243, https://doi.org/10.5194/wes-10-227-2025, https://doi.org/10.5194/wes-10-227-2025, 2025
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This study investigates how wind turbine blades damaged by erosion, along with changing wind conditions, affect power output. Even minor blade damage can lead to significant energy losses, especially in turbulent winds. Using simulations, it was discovered that standard power data analysis methods, including time averaging, can hide these losses. This research highlights the need for better blade damage detection and careful wind data analysis to optimise wind farm performance.
Unai Gutierrez Santiago, Aemilius A. W. van Vondelen, Alfredo Fernández Sisón, Henk Polinder, and Jan-Willem van Wingerden
Wind Energ. Sci., 10, 207–225, https://doi.org/10.5194/wes-10-207-2025, https://doi.org/10.5194/wes-10-207-2025, 2025
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Knowing the loads applied to wind turbine gearboxes throughout their service life is becoming increasingly important as maintaining reliability with higher torque density demands is proving to be challenging. Operational deflection shapes identified from fiber-optic strain measurements have enabled the estimation of input torque, improving the assessment of the consumed life. Tracking operational deflection shapes recursively over time can potentially be used as an indicator of fault detection.
Kenneth Brown, Pietro Bortolotti, Emmanuel Branlard, Mayank Chetan, Scott Dana, Nathaniel deVelder, Paula Doubrawa, Nicholas Hamilton, Hristo Ivanov, Jason Jonkman, Christopher Kelley, and Daniel Zalkind
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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This paper presents a study of the popular wind turbine design tool OpenFAST. We compare simulation results to measurements obtained from a 2.8 MW land-based wind turbine. Measured wind conditions were used to generate turbulent flow fields through several techniques. We show that successful validation of the tool is not strongly dependent on the inflow generation technique used for mean quantities of interest. The type of inflow assimilation method has a larger effect on fatigue quantities.
Fiona Dominique Lüdecke, Martin Schmid, and Po Wen Cheng
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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Large direct-drive wind turbines, with a multi-megawatt power rating, face design challenges. Moving towards a more system-oriented design approach could potentially reduce mass and costs. Exploiting the full design space, though, may invoke interaction mechanisms, which have been neglected in the past. Based on coupled simulations, this work derives a better understanding of the electro-mechanical interaction mechanisms and identifies potential for design relevance.
Jenna Iori, Carlo Luigi Bottasso, and Michael Kenneth McWilliam
Wind Energ. Sci., 9, 1289–1304, https://doi.org/10.5194/wes-9-1289-2024, https://doi.org/10.5194/wes-9-1289-2024, 2024
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The controller of a wind turbine has an important role in regulating power production and avoiding structural failure. However, it is often designed after the rest of the turbine, and thus its potential is not fully exploited. An alternative is to design the structure and the controller simultaneously. This work develops a method to identify if a given turbine design can benefit from this new simultaneous design process. For example, a higher and cheaper turbine tower can be built this way.
Andrea Gamberini, Thanasis Barlas, Alejandro Gomez Gonzalez, and Helge Aagaard Madsen
Wind Energ. Sci., 9, 1229–1249, https://doi.org/10.5194/wes-9-1229-2024, https://doi.org/10.5194/wes-9-1229-2024, 2024
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Movable surfaces on wind turbine (WT) blades, called active flaps, can reduce the cost of wind energy. However, they still need extensive testing. This study shows that the computer model used to design a WT with flaps aligns well with measurements obtained from a 3month test on a commercial WT featuring a prototype flap. Particularly during flap actuation, there were minimal differences between simulated and measured data. These findings assure the reliability of WT designs incorporating flaps.
Ruben Borgers, Marieke Dirksen, Ine L. Wijnant, Andrew Stepek, Ad Stoffelen, Naveed Akhtar, Jérôme Neirynck, Jonas Van de Walle, Johan Meyers, and Nicole P. M. van Lipzig
Wind Energ. Sci., 9, 697–719, https://doi.org/10.5194/wes-9-697-2024, https://doi.org/10.5194/wes-9-697-2024, 2024
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Wind farms at sea are becoming more densely clustered, which means that next to individual wind turbines interfering with each other in a single wind farm also interference between wind farms becomes important. Using a climate model, this study shows that the efficiency of wind farm clusters and the interference between the wind farms in the cluster depend strongly on the properties of the individual wind farms and are also highly sensitive to the spacing between the wind farms.
Javier Criado Risco, Rafael Valotta Rodrigues, Mikkel Friis-Møller, Julian Quick, Mads Mølgaard Pedersen, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 585–600, https://doi.org/10.5194/wes-9-585-2024, https://doi.org/10.5194/wes-9-585-2024, 2024
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Wind energy developers frequently have to face some spatial restrictions at the time of designing a new wind farm due to different reasons, such as the existence of protected natural areas around the wind farm location, fishing routes, and the presence of buildings. Wind farm design has to account for these restricted areas, but sometimes this is not straightforward to achieve. We have developed a methodology that allows for different inclusion and exclusion areas in the optimization framework.
Amalia Ida Hietanen, Thor Heine Snedker, Katherine Dykes, and Ilmas Bayati
Wind Energ. Sci., 9, 417–438, https://doi.org/10.5194/wes-9-417-2024, https://doi.org/10.5194/wes-9-417-2024, 2024
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The layout of a floating offshore wind farm was optimized to maximize the relative net present value (NPV). By modeling power generation, losses, inter-array cables, anchors and operational costs, an increase of EUR 34.5 million in relative NPV compared to grid-based layouts was achieved. A sensitivity analysis was conducted to examine the impact of economic factors, providing valuable insights. This study contributes to enhancing the efficiency and cost-effectiveness of floating wind farms.
Rafael Valotta Rodrigues, Mads Mølgaard Pedersen, Jens Peter Schøler, Julian Quick, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 321–341, https://doi.org/10.5194/wes-9-321-2024, https://doi.org/10.5194/wes-9-321-2024, 2024
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The use of wind energy has been growing over the last few decades, and further increase is predicted. As the wind energy industry is starting to consider larger wind farms, the existing numerical methods for analysis of small and medium wind farms need to be improved. In this article, we have explored different strategies to tackle the problem in a feasible and timely way. The final product is a set of recommendations when carrying out trade-off analysis on large wind farms.
Aiguo Zhou, Jinlei Shi, Tao Dong, Yi Ma, and Zhenhui Weng
Wind Energ. Sci., 9, 49–64, https://doi.org/10.5194/wes-9-49-2024, https://doi.org/10.5194/wes-9-49-2024, 2024
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This paper explores the nonlinear influence of the virtual mass mechanism on the test system in blade biaxial tests. The blade theory and simulation model are established to reveal the nonlinear amplitude–frequency characteristics of the blade-virtual-mass system. Increasing the amplitude of the blade or decreasing the seesaw length will lower the resonance frequency and load of the system. The virtual mass also affects the blade biaxial trajectory.
Xiaodong Zhang and Nikolay Dimitrov
Wind Energ. Sci., 8, 1613–1623, https://doi.org/10.5194/wes-8-1613-2023, https://doi.org/10.5194/wes-8-1613-2023, 2023
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Wind turbine extreme response estimation based on statistical extrapolation necessitates using a small number of simulations to calculate a low exceedance probability. This is a challenging task especially if we require small prediction error. We propose the use of a Gaussian mixture model as it is capable of estimating a low exceedance probability with minor bias error, even with limited simulation data, having flexibility in modeling the distributions of varying response variables.
Arne Bartschat, Karsten Behnke, and Matthias Stammler
Wind Energ. Sci., 8, 1495–1510, https://doi.org/10.5194/wes-8-1495-2023, https://doi.org/10.5194/wes-8-1495-2023, 2023
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Blade bearings are among the most stressed and challenging components of a wind turbine. Experimental investigations using different test rigs and real-size blade bearings have been able to show that rather short time intervals of only several hours of turbine operation can cause wear damage on the raceways of blade bearings. The proposed methods can be used to assess wear-critical operation conditions and to validate control strategies as well as lubricants for the application.
Juan-Andrés Pérez-Rúa, Mathias Stolpe, and Nicolaos Antonio Cutululis
Wind Energ. Sci., 8, 1453–1473, https://doi.org/10.5194/wes-8-1453-2023, https://doi.org/10.5194/wes-8-1453-2023, 2023
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With the challenges of ensuring secure energy supplies and meeting climate targets, wind energy is on course to become the cornerstone of decarbonized energy systems. This work proposes a new method to optimize wind farms by means of smartly placing wind turbines within a given project area, leading to more green-energy generation. This method performs satisfactorily compared to state-of-the-art approaches in terms of the resultant annual energy production and other high-level metrics.
Andrew P. J. Stanley, Christopher J. Bay, and Paul Fleming
Wind Energ. Sci., 8, 1341–1350, https://doi.org/10.5194/wes-8-1341-2023, https://doi.org/10.5194/wes-8-1341-2023, 2023
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Better wind farms can be built by simultaneously optimizing turbine locations and control, which is currently impossible or extremely challenging because of the size of the problem. The authors present a method to determine optimal wind farm control as a function of the turbine locations, which enables turbine layout and control to be optimized together by drastically reducing the size of the problem. In an example, a wind farm's performance improves by 0.8 % when optimized with the new method.
Maaike Sickler, Bart Ummels, Michiel Zaaijer, Roland Schmehl, and Katherine Dykes
Wind Energ. Sci., 8, 1225–1233, https://doi.org/10.5194/wes-8-1225-2023, https://doi.org/10.5194/wes-8-1225-2023, 2023
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This paper investigates the effect of wind farm layout on the performance of offshore wind farms. A regular farm layout is compared to optimised irregular layouts. The irregular layouts have higher annual energy production, and the power production is less sensitive to wind direction. However, turbine towers require thicker walls to counteract increased fatigue due to increased turbulence levels in the farm. The study shows that layout optimisation can be used to maintain high-yield performance.
Nicholas Peters, Christopher Silva, and John Ekaterinaris
Wind Energ. Sci., 8, 1201–1223, https://doi.org/10.5194/wes-8-1201-2023, https://doi.org/10.5194/wes-8-1201-2023, 2023
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Wind turbines have increasingly been leveraged as a viable approach for obtaining renewable energy. As such, it is essential that engineers have a high-fidelity, low-cost approach to modeling rotor load distributions. In this study, such an approach is proposed. This modeling approach was shown to make high-fidelity predictions at a low computational cost for rotor distributed-pressure loads as rotor geometry varied, allowing for an optimization of the rotor to be completed.
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.
Kisorthman Vimalakanthan, Harald van der Mijle Meijer, Iana Bakhmet, and Gerard Schepers
Wind Energ. Sci., 8, 41–69, https://doi.org/10.5194/wes-8-41-2023, https://doi.org/10.5194/wes-8-41-2023, 2023
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Leading edge erosion (LEE) is one of the most critical degradation mechanisms that occur with wind turbine blades. A detailed understanding of the LEE process and the impact on aerodynamic performance due to the damaged leading edge is required to optimize blade maintenance. Providing accurate modeling tools is therefore essential. This novel study assesses CFD approaches for modeling high-resolution scanned LE surfaces from an actual blade with LEE damages.
Paul Veers, Katherine Dykes, Sukanta Basu, Alessandro Bianchini, Andrew Clifton, Peter Green, Hannele Holttinen, Lena Kitzing, Branko Kosovic, Julie K. Lundquist, Johan Meyers, Mark O'Malley, William J. Shaw, and Bethany Straw
Wind Energ. Sci., 7, 2491–2496, https://doi.org/10.5194/wes-7-2491-2022, https://doi.org/10.5194/wes-7-2491-2022, 2022
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Wind energy will play a central role in the transition of our energy system to a carbon-free future. However, many underlying scientific issues remain to be resolved before wind can be deployed in the locations and applications needed for such large-scale ambitions. The Grand Challenges are the gaps in the science left behind during the rapid growth of wind energy. This article explains the breadth of the unfinished business and introduces 10 articles that detail the research needs.
Alessandro Bianchini, Galih Bangga, Ian Baring-Gould, Alessandro Croce, José Ignacio Cruz, Rick Damiani, Gareth Erfort, Carlos Simao Ferreira, David Infield, Christian Navid Nayeri, George Pechlivanoglou, Mark Runacres, Gerard Schepers, Brent Summerville, David Wood, and Alice Orrell
Wind Energ. Sci., 7, 2003–2037, https://doi.org/10.5194/wes-7-2003-2022, https://doi.org/10.5194/wes-7-2003-2022, 2022
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The paper is part of the Grand Challenges Papers for Wind Energy. It provides a status of small wind turbine technology in terms of technical maturity, diffusion, and cost. Then, five grand challenges that are thought to be key to fostering the development of the technology are proposed. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Improvement areas are highlighted, within which 10 key enabling actions are finally proposed to the wind community.
Mads H. Aa. Madsen, Frederik Zahle, Sergio González Horcas, Thanasis K. Barlas, and Niels N. Sørensen
Wind Energ. Sci., 7, 1471–1501, https://doi.org/10.5194/wes-7-1471-2022, https://doi.org/10.5194/wes-7-1471-2022, 2022
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This work presents a shape optimization framework based on computational fluid dynamics. The design framework is used to optimize wind turbine blade tips for maximum power increase while avoiding that extra loading is incurred. The final results are shown to align well with related literature. The resulting tip shape could be mounted on already installed wind turbines as a sleeve-like solution or be conceived as part of a modular blade with tips designed for site-specific conditions.
Edward Hart, Adam Stock, George Elderfield, Robin Elliott, James Brasseur, Jonathan Keller, Yi Guo, and Wooyong Song
Wind Energ. Sci., 7, 1209–1226, https://doi.org/10.5194/wes-7-1209-2022, https://doi.org/10.5194/wes-7-1209-2022, 2022
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We consider characteristics and drivers of loads experienced by wind turbine main bearings using simplified models of hub and main-bearing configurations. Influences of deterministic wind characteristics are investigated for 5, 7.5, and 10 MW turbine models. Load response to gusts and wind direction changes are also considered. Cubic load scaling is observed, veer is identified as an important driver of load fluctuations, and strong links between control and main-bearing load response are shown.
Cited articles
Agarwala, R. and Ro, P. I.: Separated Pitch Control at Tip: Innovative Blade Design Explorations for Large MW Wind Turbine Blades, Journal of Wind Energy, 2015, 1–12, https://doi.org/10.1155/2015/895974, 2015. a
Barter, G. E., Sethuraman, L., Bortolotti, P., Keller, J., and Torrey, D. A.: Beyond 15 MW: A cost of energy perspective on the next generation of drivetrain technologies for offshore wind turbines, Appl. Energ., 344, 121272, https://doi.org/10.1016/j.apenergy.2023.121272, 2023. a
Baumgärtner, D., Borowski, J., Deters, C., Dietrich, E., Dörenkämper, M., Fricke, J., Hans, F., Jersch, T., Leimeister, M., Meyer, T., Neshati, M., Pangalos, G., Quiroz, T., Quistorf, G., Requate, N., Schmidt, J., Schnackenberg, M., Schwegmann, S., Spill, S., Thomas, P., Vollmer, L., Walgern, J., and Widerspan, V.: Weiterentwicklung der Rahmenbedingungen zur Planung von Windenergieanlagen auf See und Netzanbindungssystemen: Endbericht, Fraunhofer IWES, Bremerhaven, https://doi.org/10.24406/publica-2202, 2021. a, b
Berg, J. and Resor, B.: Numerical Manufacturing And Design Tool (NuMAD v2.0) for Wind Turbine Blades: User's Guide, Sandia Report, SAND2012-7028, Albuquerque, https://doi.org/10.2172/1051715, 2012. a
Bir, G.: User's Guide to PreComp (Pre-Processor for Computing Composite Blade Properties), National Renewable Energy Laboratory, NREL/TP-500-38929, Golden (US), https://doi.org/10.2172/876556, 2005. a
Bolinger, M., Lantz, E., Wiser, R., Hoen, B., Rand, J., and Hammond, R.: Opportunities for and challenges to further reductions in the “specific power” rating of wind turbines installed in the United States, Wind Engineering, 45, 351–368, https://doi.org/10.1177/0309524X19901012, 2021. a
Bortolotti, P., Berry, D., Murray, R., Gaertner, E., Jenne, D., Damiani, R., Barter, G., and Dykes, K.: A Detailed Wind Turbine Blade Cost Model, National Renewable Energy Laboratory, NREL/TP-5000-73585, https://doi.org/10.2172/1529217, 2019. a
Branlard, E., Jonkman, B., Pirrung, G. R., Dixon, K., and Jonkman, J.: Dynamic inflow and unsteady aerodynamics models for modal and stability analyses in OpenFAST, J. Phys. Conf. Ser., 2265, 032044, https://doi.org/10.1088/1742-6596/2265/3/032044, 2022. a
Buhl, L.: New Empirical Relationship between Thrust Coefficient and Induction Factor for the Turbulent Windmill State, National Renewable Energy Laboratory, NREL/TP-500-36834, https://doi.org/10.2172/15016819, 2005. a
Chaviaropoulos, P. K. and Sieros, G.: Design of low induction rotors for use in large offshore wind farms, EWEA Conf., 10–13 March 2014, Barcelona, https://www.researchgate.net/publication/263209536_Design_of_Low_Induction_Rotors_for_use_in_large_offshore_wind_farms (last access: 15 November 2023), 2014. a
Damiani, R. and Hayman, G.: The Unsteady Aerodynamics Module for FAST 8, National Renewable Energy Laboratory, NREL/TP-5000-66347, https://doi.org/10.2172/1576488, 2019. a
Det Norske Veritas group: DNV-ST-0437 Loads and site conditions for wind turbines, standard, https://www.dnv.com/energy/standards-guidelines/dnv-st-0437-loads-and-site-conditions-for-wind-turbines.html (last access: 15 November 2023), November 2016 (amended: November 2021). a
Dykes, K., Kitzing, L., Andersson, M., Pons-Seres de Brauwer, C., and Canét, H.: Beyond LCOE: New Assessment Criteria for Evaluating Wind Energy R&I: A SETWind workshop report, Brussels, 23–24 January 2020, https://backend.orbit.dtu.dk/ws/portalfiles/portal/234026713/Beyond_LCOE_New_Assessment_Criteria_for_Evaluating_Wind_Energy_RI.pdf (last access: 15 November 2023), 2020. a
Dykes, K., Ning, S. A., Scott, G., and Graf, P.: WISDEM® (Wind-Plant Integrated System Design and Engineering Model), DOE Code [code], https://doi.org/10.11578/dc.20211208.2, 2021. a
Federal Maritime and Hydrographic Agency of Germany: Flächenentwicklungsplan 2020 für die deutsche Nord- und Ostsee, BSH 7608, Hamburg, https://www.bsh.de/DE/THEMEN/Offshore/Meeresfachplanung/Flaechenentwicklungsplan/_Anlagen/Downloads/Downloads_Publikationsslider/FEP_2020_Flaechenentwicklungsplan_2020.pdf?__blob=publicationFile&v=6 (last access: 15 November 2023), 2020. a
Feil, R., Abbas, N., Bortolotti, P., Johnson, N., and Mertz, B.: Distributed Aerodynamic Control using Active Trailing-Edge Flaps for Large Wind Turbines, J. Phys. Conf. Ser., 1618, 042026, https://doi.org/10.1088/1742-6596/1618/4/042026, 2020. a
Fingersh, L., Hand, M., and Laxson, A.: Wind Turbine Design Cost and Scaling Model, National Renewable Energy Laboratory, NREL/TP-500-40566, https://doi.org/10.2172/897434, 2006. a, b
Gaertner, E., Rinker, J., Sethuraman, L., Zahle, F., Anderson, B., Barter, G., Abbas, N., Meng, F., Bortolotti, P., Skrzypinski, W., Scott, G., Feil, R., Bredmose, H., Dykes, K., Shields, M., Allen, C., and Viselli, A.: Definition of the IEA 15-Megawatt Offshore Reference Wind turbine, NREL/TP-5000-75698, National Renewable Energy Laboratory, Golden (US), https://doi.org/10.2172/1603478, 2020. a, b
Gasch, R. and Twele, J.: Wind Power Plants: Fundamentals, Design, Construction and Operation, 2nd edn., Springer, Berlin, https://doi.org/10.1007/978-3-642-22938-1, 2012. a, b, c, d
Griffith, T. and Richards, P.: The SNL100-03 Blade: Design Studies with Flatback Airfoils for the Sandia 100 m Blade, Sandia Report, SAND2014-18129, https://doi.org/10.2172/1159116, 2014. a
Hand, M., Hethey, A., Lüers, S., Wallasch, A., Rehfeldt, K., Duffy, A., Weir, D., Stenkvist, M., Uihlein, A., Stehly, T., Lantz, E., and Wiser, R.: IEA Wind TCP Task 26 – Wind Technology, Cost, and Performance Trends in Denmark, Germany, Ireland, Norway, Sweden, the European Union, and the United States: 2008–2016, National Renewable Energy Laboratory, NREL/TP-6A20-71844, Golden (US), https://doi.org/10.2172/1525772, 2018. a
Hirth, L. and Müller, S.: System-friendly wind power, Energ. Econ., 56, 51–63, https://doi.org/10.1016/j.eneco.2016.02.016, 2016. a
Jamieson, P.: Top-level rotor optimisations based on actuator disc theory, Wind Energ. Sci., 5, 807–818, https://doi.org/10.5194/wes-5-807-2020, 2020. a, b, c
Jamieson, P., Hornzee-Jones, C., Moroz, E., and Blakemore, R.: Variable diameter wind turbine rotor blades, US patent: US 6,972,498 B2, 2005. a
Johnson, N., Bortolotti, P., Dykes, K., Barter, G., Moriarty, P., Carron, S., Wendt, F., Veers, P., Paquette, J., Kelly, C., and Ennis, B.: Investigation of Innovative Rotor Concepts for the Big Adaptive Rotor Project, National Renewable Energy Laboratory, NREL/TP-5000-73605, https://doi.org/10.2172/1563139, 2019. a
Johnson, N., Paquette, J., Bortolotti, P., Mendoza, N., Bolinger, M., Camarena, E., Anderson, E., and Ennis, B.: Big Adaptive Rotor Phase I Final Report, National Renewable Energy Laboratory, NREL/TP-5000-79855, https://doi.org/10.2172/1835259, 2021. a
Jonkman, B., Mudafort, R., Platt, A., Branlard, E., Sprague, M., Vijayakumar, G., Buhl, M., Ross, H., Bortolotti, P., Masciola, M., Ananthan, D., Schmidt, M., Rood, J., Hall, M., Bendl, K., and Martinez, T.: OpenFAST release v3.1.0, Zenodo [code], https://doi.org/10.5281/zenodo.6324288, 2022. a
López Prol, J., Steininger, K. W., and Zilberman, D.: The cannibalization effect of wind and solar in the California wholesale electricity market, Energ. Econ., 85, 104552, https://doi.org/10.1016/j.eneco.2019.104552, 2020. a
Madsen, H. A., Zahle, F., Meng, F., Barlas, T., Rasmussen, F., and Rudolf, R. T.: Initial performance and load analysis of the LowWind turbine in comparison with a conventional turbine, J. Phys. Conf. Ser., 1618, 032011, https://doi.org/10.1088/1742-6596/1618/3/032011, 2020. a, b, c
Noyes, C., Qin, C., and Loth, E.: Analytic analysis of load alignment for coning extreme–scale rotors, Wind Energy, 23, 357–369, https://doi.org/10.1002/we.2435, 2020. a
Pettas, V., Kretschmer, M., Clifton, A., and Cheng, P. W.: On the effects of inter-farm interactions at the offshore wind farm Alpha Ventus, Wind Energ. Sci., 6, 1455–1472, https://doi.org/10.5194/wes-6-1455-2021, 2021. a
Qin, C., Loth, E., Zalkind, D. S., Pao, L. Y., Yao, S., Griffith, D. T., Selig, M. S., and Damiani, R.: Downwind coning concept rotor for a 25 MW offshore wind turbine, Renew. Energ., 156, 314–327, https://doi.org/10.1016/j.renene.2020.04.039, 2020. a
Ribnitzky, D.: Hybrid-Lambda Rotor (low specific rating offshore wind turbine) – simulation model, Zenodo [data set], https://doi.org/10.5281/zenodo.10406459, 2023. a
Ribnitzky, D., Berger, F., and Kühn, M.: Innovative aerodynamic rotor concept for demand-oriented power feed-in of offshore wind turbines, J. Phys. Conf. Ser., 2265, 032017, https://doi.org/10.1088/1742-6596/2265/3/032017, 2022. a
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Short summary
This paper provides an innovative blade design methodology for offshore wind turbines with very large rotors compared to their rated power, which are tailored for an increased power feed-in at low wind speeds. Rather than designing the blade for a single optimized operational point, we include the application of peak shaving in the design process and introduce a design for two tip speed ratios. We describe how enlargement of the rotor diameter can be realized to improve the value of wind power.
This paper provides an innovative blade design methodology for offshore wind turbines with very...
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