Articles | Volume 6, issue 3
https://doi.org/10.5194/wes-6-917-2021
© 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-6-917-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
10 Jun 2021
Research article |
| 10 Jun 2021
| 10 Jun 2021
A method for preliminary rotor design – Part 2: Wind turbine Optimization with Radial Independence
Suzlon Blade Science Center, Brendstrupgaardsvej 13, 8210 Aarhus, Denmark
Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Christian Bak
Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
Michael McWilliam
Technical University of Denmark, Frederiksborgvej 399, 4000 Roskilde, Denmark
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Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Michael McWilliam
Wind Energ. Sci., 6, 903–915, https://doi.org/10.5194/wes-6-903-2021, https://doi.org/10.5194/wes-6-903-2021, 2021
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We present a model for assessing the aerodynamic performance of a wind turbine rotor through a different parametrization of the classical blade element momentum model. The model establishes an analytical relationship between the loading in the flow direction and the power along the rotor span. The main benefit of the model is the ease with which it can be applied for rotor optimization and especially load constraint power optimization.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Bjarke Dam
Wind Energ. Sci., 5, 155–170, https://doi.org/10.5194/wes-5-155-2020, https://doi.org/10.5194/wes-5-155-2020, 2020
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From the basic aerodynamic theory of wind turbine rotors, it is a well-known fact that there is a relationship between the loading of the rotor and power efficiency. It shows that there is a loading that maximizes the power efficiency, and it is common to target this maximum when designing rotors. But in this paper it is found that for rotors constrained by a load, the maximum power is found by decreasing the loading and increasing the rotor radius. Max power efficiency is therefore not optimal.
Tahir H. Malik and Christian Bak
Wind Energ. Sci., 9, 2017–2037, https://doi.org/10.5194/wes-9-2017-2024, https://doi.org/10.5194/wes-9-2017-2024, 2024
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We explore the effect of blade modifications on offshore wind turbines' performance through a detailed analysis of 12 turbines over 12 years. Introducing the turbine performance integral method, which utilises time-series decomposition that combines various data sources, we uncover how blade wear, repairs and software updates impact efficiency. The findings offer valuable insights into improving wind turbine operations, contributing to the enhancement of renewable energy technologies.
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.
Tahir H. Malik and Christian Bak
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-49, https://doi.org/10.5194/wes-2024-49, 2024
Revised manuscript accepted for WES
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This research integrates custom sensors into wind turbine simulation models for improved performance monitoring utilising a developed method. Real-world data validation demonstrates that enhanced sensor accuracy increases annual energy production and extends operational lifespan. 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. Discuss., https://doi.org/10.5194/wes-2024-35, https://doi.org/10.5194/wes-2024-35, 2024
Revised manuscript accepted for WES
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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, we 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 optimize wind farm performance.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Michael McWilliam
Wind Energ. Sci., 6, 903–915, https://doi.org/10.5194/wes-6-903-2021, https://doi.org/10.5194/wes-6-903-2021, 2021
Short summary
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We present a model for assessing the aerodynamic performance of a wind turbine rotor through a different parametrization of the classical blade element momentum model. The model establishes an analytical relationship between the loading in the flow direction and the power along the rotor span. The main benefit of the model is the ease with which it can be applied for rotor optimization and especially load constraint power optimization.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Bjarke Dam
Wind Energ. Sci., 5, 155–170, https://doi.org/10.5194/wes-5-155-2020, https://doi.org/10.5194/wes-5-155-2020, 2020
Short summary
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From the basic aerodynamic theory of wind turbine rotors, it is a well-known fact that there is a relationship between the loading of the rotor and power efficiency. It shows that there is a loading that maximizes the power efficiency, and it is common to target this maximum when designing rotors. But in this paper it is found that for rotors constrained by a load, the maximum power is found by decreasing the loading and increasing the rotor radius. Max power efficiency is therefore not optimal.
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.
Michael K. McWilliam, Thanasis K. Barlas, Helge A. Madsen, and Frederik Zahle
Wind Energ. Sci., 3, 231–241, https://doi.org/10.5194/wes-3-231-2018, https://doi.org/10.5194/wes-3-231-2018, 2018
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Maximizing wind energy production is challenging because the winds are always changing. Design optimization was used to explore how flaps can give rotor design engineers greater ability to adapt the rotor for different conditions. For rotors designed for peak efficiency (i.e. older designs) the flap adds 0.5 % improvement in energy production. However, for modern designs that optimize both the performance and the structure, the flap can provide a 1 % improvement.
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Optimal scheduling of the next preventive maintenance activity for a wind farm
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Wind Energ. Sci., 7, 991–1006, https://doi.org/10.5194/wes-7-991-2022, https://doi.org/10.5194/wes-7-991-2022, 2022
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Andrew P. J. Stanley, Christopher Bay, Rafael Mudafort, and Paul Fleming
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Andrew P. J. Stanley, Jennifer King, Christopher Bay, and Andrew Ning
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Mareike Leimeister, Maurizio Collu, and Athanasios Kolios
Wind Energ. Sci., 7, 259–281, https://doi.org/10.5194/wes-7-259-2022, https://doi.org/10.5194/wes-7-259-2022, 2022
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Floating offshore wind technology has high potential but still faces challenges for gaining economic competitiveness to allow commercial market uptake. Hence, design optimization plays a key role; however, the final optimum floater obtained highly depends on the specified optimization problem. Thus, by considering alternative structural realization approaches, not very stringent limitations on the structure and dimensions are required. This way, more innovative floater designs can be captured.
Ernesto Camarena, Evan Anderson, Josh Paquette, Pietro Bortolotti, Roland Feil, and Nick Johnson
Wind Energ. Sci., 7, 19–35, https://doi.org/10.5194/wes-7-19-2022, https://doi.org/10.5194/wes-7-19-2022, 2022
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Ye Liu, Yun Qian, and Larry K. Berg
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Alessandro Croce, Stefano Cacciola, and Luca Sartori
Wind Energ. Sci., 7, 1–17, https://doi.org/10.5194/wes-7-1-2022, https://doi.org/10.5194/wes-7-1-2022, 2022
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In this work we have analyzed the effects of these recent technologies on a single wind turbine, with the aim of understanding the impact of these controllers on the design of the machine itself.
The analyses have shown there are non-negligible effects on some components of the wind turbine.
Nicola Bodini, Weiming Hu, Mike Optis, Guido Cervone, and Stefano Alessandrini
Wind Energ. Sci., 6, 1363–1377, https://doi.org/10.5194/wes-6-1363-2021, https://doi.org/10.5194/wes-6-1363-2021, 2021
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We develop two machine-learning-based approaches to temporally extrapolate uncertainty in hub-height wind speed modeled by a numerical weather prediction model. We test our approaches in the California Outer Continental Shelf, where a significant offshore wind energy development is currently being planned, and we find that both provide accurate results.
Helena Canet, Stefan Loew, and Carlo L. Bottasso
Wind Energ. Sci., 6, 1325–1340, https://doi.org/10.5194/wes-6-1325-2021, https://doi.org/10.5194/wes-6-1325-2021, 2021
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Lidar-assisted control (LAC) is used to redesign the rotor and tower of three turbines, differing in terms of wind class, size, and power rating. The load reductions enabled by LAC are used to save
mass, increase hub height, or extend lifetime. The first two strategies yield reductions in the cost of energy only for the tower of the largest machine, while more interesting benefits are obtained for lifetime extension.
David Getz and Jose Palacios
Wind Energ. Sci., 6, 1291–1309, https://doi.org/10.5194/wes-6-1291-2021, https://doi.org/10.5194/wes-6-1291-2021, 2021
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A methodology to design electrothermal deicing protection for wind turbines is presented. The method relies on modeling and experimental testing to determine the critical ice thickness. The critical ice thickness needed is dependent on the ice tensile strength, which varies with icing conditions. The ice tensile strength must be overcome by the stress that a de-bonded ice structure exerts under centrifugal force at its root region, where it attaches to a non-de-bonded ice region.
Pietro Bortolotti, Nick Johnson, Nikhar J. Abbas, Evan Anderson, Ernesto Camarena, and Joshua Paquette
Wind Energ. Sci., 6, 1277–1290, https://doi.org/10.5194/wes-6-1277-2021, https://doi.org/10.5194/wes-6-1277-2021, 2021
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The length of rotor blades of land-based wind turbines is currently constrained by logistics. Turbine manufacturers currently propose segmented solutions to overcome these limits, but blade joints come with extra masses and costs. This work investigates an alternative solution, namely the design of ultra-flexible blades that can be transported on rail via controlled bending. The results show that this is a promising pathway for further increasing the size of land-based wind turbines.
Andrew P. J. Stanley, Owen Roberts, Jennifer King, and Christopher J. Bay
Wind Energ. Sci., 6, 1143–1167, https://doi.org/10.5194/wes-6-1143-2021, https://doi.org/10.5194/wes-6-1143-2021, 2021
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Wind farm layout optimization is an essential part of wind farm design. In this paper, we present different methods to determine the number of turbines in a wind farm, as well as their placement. Also in this paper we explore the effect that the objective function has on the wind farm design and found that wind farm layout is highly sensitive to the objective. The optimal number of turbines can vary greatly, from 15 to 54 for the cases in this paper, depending on the metric that is optimized.
Gerard Schepers, Pim van Dorp, Remco Verzijlbergh, Peter Baas, and Harmen Jonker
Wind Energ. Sci., 6, 983–996, https://doi.org/10.5194/wes-6-983-2021, https://doi.org/10.5194/wes-6-983-2021, 2021
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In this article the aeroelastic loads on a 10 MW turbine in response to unconventional wind conditions selected from a year-long large-eddy simulation on a site at the North Sea are evaluated. Thereto an assessment is made of the practical importance of these wind conditions within an aeroelastic context based on high-fidelity wind modelling. Moreover the accuracy of BEM-based methods for modelling such wind conditions is assessed.
Quanjiang Yu, Michael Patriksson, and Serik Sagitov
Wind Energ. Sci., 6, 949–959, https://doi.org/10.5194/wes-6-949-2021, https://doi.org/10.5194/wes-6-949-2021, 2021
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There are two ways to maintain a multi-component system: corrective maintenance, when a broken component is replaced with a new one, and preventive maintenance (PM), when some components are replaced in a planned manner before they break down. This article proposes a mathematical model for finding an optimal time to perform the next PM activity and selecting the components which should be replaced. The model is fast to solve, and it can be used as a key module in a maintenance scheduling app.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Michael McWilliam
Wind Energ. Sci., 6, 903–915, https://doi.org/10.5194/wes-6-903-2021, https://doi.org/10.5194/wes-6-903-2021, 2021
Short summary
Short summary
We present a model for assessing the aerodynamic performance of a wind turbine rotor through a different parametrization of the classical blade element momentum model. The model establishes an analytical relationship between the loading in the flow direction and the power along the rotor span. The main benefit of the model is the ease with which it can be applied for rotor optimization and especially load constraint power optimization.
Erik Quaeghebeur, René Bos, and Michiel B. Zaaijer
Wind Energ. Sci., 6, 815–839, https://doi.org/10.5194/wes-6-815-2021, https://doi.org/10.5194/wes-6-815-2021, 2021
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We present a technique to support the optimal layout (placement) of wind turbines in a wind farm. It efficiently determines good directions and distances for moving turbines. An improved layout reduces production losses and so makes the farm project economically more attractive. Compared to most existing techniques, our approach requires less time. This allows wind farm designers to explore more alternatives and provides the flexibility to adapt the layout to site-specific requirements.
Helena Canet, Pietro Bortolotti, and Carlo L. Bottasso
Wind Energ. Sci., 6, 601–626, https://doi.org/10.5194/wes-6-601-2021, https://doi.org/10.5194/wes-6-601-2021, 2021
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The paper analyzes in detail the problem of scaling, considering both the steady-state and transient response cases, including the effects of aerodynamics, elasticity, inertia, gravity, and actuation. After a general theoretical analysis of the problem, the article considers two alternative ways of designing a scaled rotor. The two methods are then applied to the scaling of a 10 MW turbine of 180 m in diameter down to three different sizes (54, 27, and 2.8 m).
Freia Harzendorf, Ralf Schelenz, and Georg Jacobs
Wind Energ. Sci., 6, 571–584, https://doi.org/10.5194/wes-6-571-2021, https://doi.org/10.5194/wes-6-571-2021, 2021
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Making wind turbines more reliable over their lifetime is an important goal for improving wind turbine technology. The wind turbine drivetrain has a major influence on turbine reliability. This paper presents an approach that will help to identify holistically better drivetrain concepts in an early product design phase from an operational perspective as it is able to estimate and assess drivetrain-concept-specific inherent risks in the operational phase.
Artur Movsessian, Marcel Schedat, and Torsten Faber
Wind Energ. Sci., 6, 539–554, https://doi.org/10.5194/wes-6-539-2021, https://doi.org/10.5194/wes-6-539-2021, 2021
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The assessment of the structural condition and technical lifetime extension of a wind turbine is challenging due to lack of information for the estimation of fatigue loads. This paper demonstrates the modelling of damage-equivalent loads of the fore–aft bending moments of a wind turbine tower, highlighting the advantage of using the neighbourhood component analysis. This feature selection technique is compared to correlation analysis, stepwise regression, and principal component analysis.
Jan Wiśniewski, Krzysztof Rogowski, Konrad Gumowski, and Jacek Szumbarski
Wind Energ. Sci., 6, 287–294, https://doi.org/10.5194/wes-6-287-2021, https://doi.org/10.5194/wes-6-287-2021, 2021
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The article describes results of experimental wind tunnel and CFD testing of four different straight-bladed vertical axis wind turbine model configurations. The experiment tested a novel concept of vertically dividing and azimuthally shifting a turbine rotor into two parts with a specific uneven height division in order to limit cycle amplitudes and average cycle values of bending moments at the bottom of the turbine shaft to increase product lifetime, especially for industrial-scale turbines.
Gesine Wanke, Leonardo Bergami, Frederik Zahle, and David Robert Verelst
Wind Energ. Sci., 6, 203–220, https://doi.org/10.5194/wes-6-203-2021, https://doi.org/10.5194/wes-6-203-2021, 2021
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This article regards a rotor redesign for a wind turbine in upwind and in downwind rotor configurations. A simple optimization tool is used to estimate the aerodynamic planform, as well as the structural mass distribution of the rotor blade. The designs are evaluated in full load base calculations according to the IEC standard with the aeroelastic tool HAWC2. A scaling model is used to scale turbine and energy costs from the design loads and compare the costs for the turbine configurations.
Oliver Menck, Matthias Stammler, and Florian Schleich
Wind Energ. Sci., 5, 1743–1754, https://doi.org/10.5194/wes-5-1743-2020, https://doi.org/10.5194/wes-5-1743-2020, 2020
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Blade bearings of wind turbines experience unusual loads compared to bearings in other industrial applications, which adds some difficulty to the application of otherwise well-established calculation methods, like fatigue lifetime. As a result, different methods for such calculations can be found in the literature. This paper compares three approaches of varying complexity and comes to the conclusion that the simplest of the methods is very inaccurate compared to the more complex methods.
Gianluca Zorzi, Amol Mankar, Joey Velarde, John D. Sørensen, Patrick Arnold, and Fabian Kirsch
Wind Energ. Sci., 5, 1521–1535, https://doi.org/10.5194/wes-5-1521-2020, https://doi.org/10.5194/wes-5-1521-2020, 2020
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Storms, typhoons or seismic actions are likely to cause permanent rotation of offshore wind turbine foundations. Excessive rotation jeopardizes the operation of the wind turbine. In this study geotechnical, loads and probabilistic modelling are used to develop a reliability framework for predicting the rotation of the foundation under cyclic lateral loading.
Nicola Bodini and Mike Optis
Wind Energ. Sci., 5, 1435–1448, https://doi.org/10.5194/wes-5-1435-2020, https://doi.org/10.5194/wes-5-1435-2020, 2020
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Calculations of annual energy production (AEP) and its uncertainty are critical for wind farm financial transactions. Standard industry practice assumes that different uncertainty categories within an AEP calculation are uncorrelated and can therefore be combined through a sum of squares approach. In this project, we show the limits of this assumption by performing operational AEP estimates for over 470 wind farms in the United States and propose a more accurate way to combine uncertainties.
Simon Letzgus
Wind Energ. Sci., 5, 1375–1397, https://doi.org/10.5194/wes-5-1375-2020, https://doi.org/10.5194/wes-5-1375-2020, 2020
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One of the major challenges when working with wind turbine sensor data in practice is the presence of systematic changes in signal behaviour induced by malfunctions or maintenance actions. We found that approximately every third signal is affected by such change points and introduce an algorithm which reliably detects them in a highly automated fashion. The algorithm enables the application of data-driven techniques to monitor wind turbine components using data from commonly installed sensors.
Emmanuel Branlard, Dylan Giardina, and Cameron S. D. Brown
Wind Energ. Sci., 5, 1155–1167, https://doi.org/10.5194/wes-5-1155-2020, https://doi.org/10.5194/wes-5-1155-2020, 2020
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The paper presents an application of the Kalman filtering technique to estimate loads on a wind turbine. The approach combines a mechanical model and a set of measurements to estimate signals that are not available in the measurements, such as wind speed, thrust, tower position, and tower loads. The model is severalfold faster than real time and is intended to be run online, for instance, to evaluate real-time fatigue life consumption of a field turbine using a digital twin.
Laura Schröder, Nikolay Krasimirov Dimitrov, and David Robert Verelst
Wind Energ. Sci., 5, 1007–1022, https://doi.org/10.5194/wes-5-1007-2020, https://doi.org/10.5194/wes-5-1007-2020, 2020
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We suggest a methodology for correlating loads with component reliability of turbines in wind farms by combining physical modeling with machine learning. The suggested approach is demonstrated on an offshore wind farm for comparing performance, loads and lifetime estimations against recorded main bearing failures from maintenance reports. It is found that turbines positioned at the border of the wind farm with a higher expected AEP are estimated to experience earlier main bearing failures.
João Pacheco, Silvina Guimarães, Carlos Moutinho, Miguel Marques, José Carlos Matos, and Filipe Magalhães
Wind Energ. Sci., 5, 983–996, https://doi.org/10.5194/wes-5-983-2020, https://doi.org/10.5194/wes-5-983-2020, 2020
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This paper introduces the Tocha wind farm, presents the different layouts adopted in the instrumentation of the wind turbines and shows initial results. At this preliminary stage, the capabilities of the very extensive monitoring layout are demonstrated. The results presented demonstrate the ability of the different monitoring components to track the modal parameters of the system, composed of tower and rotor, and to characterize the internal loads at the tower base and blade roots.
Gesine Wanke, Leonardo Bergami, and David Robert Verelst
Wind Energ. Sci., 5, 929–944, https://doi.org/10.5194/wes-5-929-2020, https://doi.org/10.5194/wes-5-929-2020, 2020
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Converting an upwind wind turbine into a downwind configuration is shown to come with higher edgewise loads due to lower edgewise damping. The study shows from modal displacements of a reduced-order turbine model that the interaction between the forces on the rotor, the rotor motion, and the tower torsion is the main reason for the observed damping decrease.
Malo Rosemeier and Matthias Saathoff
Wind Energ. Sci., 5, 897–909, https://doi.org/10.5194/wes-5-897-2020, https://doi.org/10.5194/wes-5-897-2020, 2020
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A huge number of wind turbines have reached their designated lifetime of 20 years.
Most of the turbines installed were overdesigned.
In practice, these turbines could potentially operate longer to increase the energy yield.
For the use case turbine considered in this work, a simple lifetime extension of 8.7 years increases the energy yield by 43.5 %. When the swept rotor area is increased by means of a blade tip extension, the yield is increased by an additional 2.3 %.
Sebastian Perez-Becker, Francesco Papi, Joseph Saverin, David Marten, Alessandro Bianchini, and Christian Oliver Paschereit
Wind Energ. Sci., 5, 721–743, https://doi.org/10.5194/wes-5-721-2020, https://doi.org/10.5194/wes-5-721-2020, 2020
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Aeroelastic design load calculations play a key role in determining the design loads of the different wind turbine components. This study compares load estimations from calculations using a Blade Element Momentum aerodynamic model with estimations from calculations using a higher-order Lifting-Line Free Vortex Wake aerodynamic model. The paper finds and explains the differences in fatigue and extreme turbine loads for power production simulations that cover a wide range of turbulent wind speeds.
Kwangtae Ha, Moritz Bätge, David Melcher, and Steffen Czichon
Wind Energ. Sci., 5, 591–599, https://doi.org/10.5194/wes-5-591-2020, https://doi.org/10.5194/wes-5-591-2020, 2020
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This paper outlines a novel segment test methodology for wind turbine rotor blades. It mainly aims at improving the efficiency of the fatigue test as a future test method at Fraunhofer IWES. The numerical simulation reveals that this method has a significant time savings of up to 43 % and 52 % for 60 and 90 m blades, while improving test quality within an acceptable range of overload. This test methodology could be a technical solution for future offshore rotor blades longer than 100 m.
Jaime Liew, Albert M. Urbán, and Søren Juhl Andersen
Wind Energ. Sci., 5, 427–437, https://doi.org/10.5194/wes-5-427-2020, https://doi.org/10.5194/wes-5-427-2020, 2020
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In wind farms, the interaction between neighboring turbines can cause notable power losses. The focus of the paper is on how the combination of turbine yaw misalignment and wake effects influences the power loss in a wind turbine. The results of the paper show a more notable power loss due to turbine misalignment when turbines are closely spaced. The presented conclusions enable better predictions of a turbine's power production, which can assist the wind farm design process.
Julian Quick, Jennifer King, Ryan N. King, Peter E. Hamlington, and Katherine Dykes
Wind Energ. Sci., 5, 413–426, https://doi.org/10.5194/wes-5-413-2020, https://doi.org/10.5194/wes-5-413-2020, 2020
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We investigate the trade-offs in optimization of wake steering strategies, where upstream turbines are positioned to deflect wakes away from downstream turbines, with a probabilistic perspective. We identify inputs that are sensitive to uncertainty and demonstrate a realistic optimization under uncertainty for a wind power plant control strategy. Designing explicitly around uncertainty yielded control strategies that were generally less aggressive and more robust to the uncertain input.
Frederick Letson, Rebecca J. Barthelmie, and Sara C. Pryor
Wind Energ. Sci., 5, 331–347, https://doi.org/10.5194/wes-5-331-2020, https://doi.org/10.5194/wes-5-331-2020, 2020
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Wind turbine blade leading edge erosion (LEE) is potentially a significant source of energy loss and expense for wind farm operators. This study presents a novel approach to characterizing LEE potential from precipitation across the contiguous USA based on publicly available National Weather Service dual-polarization RADAR data. The approach is described in detail and illustrated using six locations distributed across parts of the USA that have substantial wind turbine deployments.
Erik Quaeghebeur, Sebastian Sanchez Perez-Moreno, and Michiel B. Zaaijer
Wind Energ. Sci., 5, 259–284, https://doi.org/10.5194/wes-5-259-2020, https://doi.org/10.5194/wes-5-259-2020, 2020
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The design and management of an offshore wind farm involve expertise in many disciplines. It is hard for a single person to maintain the overview needed. Therefore, we have created WESgraph, a knowledge base for the wind farm domain, implemented as a graph database. It stores descriptions of the multitude of domain concepts and their various interconnections. It allows users to explore the domain and search for relationships within and across disciplines, enabling various applications.
Lars Einar S. Stieng and Michael Muskulus
Wind Energ. Sci., 5, 171–198, https://doi.org/10.5194/wes-5-171-2020, https://doi.org/10.5194/wes-5-171-2020, 2020
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We present a framework for reducing the cost of support structures for offshore wind turbines that takes into account the many uncertainties that go into the design process. The results demonstrate how an efficient new approach, tailored for support structure design, allows the state of the art for design without uncertainties to be used within a framework that does include these uncertainties. This allows more realistic, and less conservative, design methods
to be used for practical design.
Kenneth Loenbaek, Christian Bak, Jens I. Madsen, and Bjarke Dam
Wind Energ. Sci., 5, 155–170, https://doi.org/10.5194/wes-5-155-2020, https://doi.org/10.5194/wes-5-155-2020, 2020
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From the basic aerodynamic theory of wind turbine rotors, it is a well-known fact that there is a relationship between the loading of the rotor and power efficiency. It shows that there is a loading that maximizes the power efficiency, and it is common to target this maximum when designing rotors. But in this paper it is found that for rotors constrained by a load, the maximum power is found by decreasing the loading and increasing the rotor radius. Max power efficiency is therefore not optimal.
Nikola Vasiljević, Andrea Vignaroli, Andreas Bechmann, and Rozenn Wagner
Wind Energ. Sci., 5, 73–87, https://doi.org/10.5194/wes-5-73-2020, https://doi.org/10.5194/wes-5-73-2020, 2020
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A WindScanner system consisting of two synchronized scanning lidars potentially represents a cost-effective solution for multipoint measurements. However, the lidar limitations and the site limitations are detrimental to the installation of lidars and number and location of measurement positions. To simplify the process of finding suitable measurement positions and lidar installation locations, a campaign planning workflow was devised. The paper describes the workflow and how it was digitalized.
Andrew P. J. Stanley and Andrew Ning
Wind Energ. Sci., 4, 663–676, https://doi.org/10.5194/wes-4-663-2019, https://doi.org/10.5194/wes-4-663-2019, 2019
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When designing a wind farm, one crucial step is finding the correct location or optimizing the location of the wind turbines to maximize power production. In the past, optimizing the turbine layout of large wind farms has been difficult because of the large number of interacting variables. In this paper, we present the boundary-grid parameterization method, which defines the layout of any wind farm with only five variables, allowing people to study and design wind farms regardless of the size.
Daniel S. Zalkind, Gavin K. Ananda, Mayank Chetan, Dana P. Martin, Christopher J. Bay, Kathryn E. Johnson, Eric Loth, D. Todd Griffith, Michael S. Selig, and Lucy Y. Pao
Wind Energ. Sci., 4, 595–618, https://doi.org/10.5194/wes-4-595-2019, https://doi.org/10.5194/wes-4-595-2019, 2019
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We present a model that both (1) reduces the computational effort involved in analyzing design trade-offs and (2) provides a qualitative understanding of the root cause of fatigue and extreme structural loads for wind turbine components from the blades to the tower base. We use this model in conjunction with design loads from high-fidelity simulations to analyze and compare the trade-offs between power capture and structural loading for large rotor concepts.
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.
Pietro Bortolotti, Helena Canet, Carlo L. Bottasso, and Jaikumar Loganathan
Wind Energ. Sci., 4, 397–406, https://doi.org/10.5194/wes-4-397-2019, https://doi.org/10.5194/wes-4-397-2019, 2019
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The paper studies the effects of uncertainties in aeroservoelastic
wind turbine models. Uncertainties are associated with the wind
inflow characteristics and the blade surface state, and they are propagated
by means of two non-intrusive methods throughout the
aeroservoelastic model of a large conceptual offshore wind
turbine. Results are compared with a brute-force extensive Monte
Carlo sampling to assess the convergence characteristics of the
non-intrusive approaches.
Andrés Santiago Padrón, Jared Thomas, Andrew P. J. Stanley, Juan J. Alonso, and Andrew Ning
Wind Energ. Sci., 4, 211–231, https://doi.org/10.5194/wes-4-211-2019, https://doi.org/10.5194/wes-4-211-2019, 2019
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We propose the use of a new method to efficiently compute the annual energy production (AEP) of a wind farm by properly handling the uncertainties in the wind direction and wind speed. We apply the new ideas to the layout optimization of a large wind farm. We show significant computational savings by reducing the number of simulations required to accurately compute and optimize the AEP of different wind farms.
Mads H. Aa. Madsen, Frederik Zahle, Niels N. Sørensen, and Joaquim R. R. A. Martins
Wind Energ. Sci., 4, 163–192, https://doi.org/10.5194/wes-4-163-2019, https://doi.org/10.5194/wes-4-163-2019, 2019
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The wind energy industry relies heavily on CFD to analyze new designs. This paper investigates a way to utilize CFD further upstream the design process where lower-fidelity methods are used. We present the first comprehensive 3-D CFD adjoint-based shape optimization of a 10 MW modern offshore wind turbine. The present work shows that, with the right tools, we can model the entire geometry, including the root, and optimize modern wind turbine rotors at the cost of a few hundred CFD evaluations.
Pietro Bortolotti, Abhinav Kapila, and Carlo L. Bottasso
Wind Energ. Sci., 4, 115–125, https://doi.org/10.5194/wes-4-115-2019, https://doi.org/10.5194/wes-4-115-2019, 2019
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The paper compares upwind and downwind three-bladed configurations
for a 10 MW wind turbine in terms of power and loads. For the
downwind case, the study also considers a load-aligned solution
with active coning. Results indicate that downwind solutions are
slightly more advantageous than upwind ones, although improvements
are small. Additionally, pre-alignment is difficult to achieve in
practice, and the active coning solution is associated with very
significant engineering challenges.
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Short summary
A novel wind turbine rotor optimization methodology is presented. Using an assumption of radial independence it is possible to obtain the Pareto-optimal relationship between power and loads through the use of KKT multipliers, leaving an optimization problem that can be solved at each radial station independently. Combining it with a simple cost function it is possible to analytically solve for the optimal power per cost with given inputs for the aerodynamics and the cost function.
A novel wind turbine rotor optimization methodology is presented. Using an assumption of radial...
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