Articles | Volume 9, issue 1
https://doi.org/10.5194/wes-9-141-2024
© 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-9-141-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Drivers for optimum sizing of wind turbines for offshore wind farms
Wind Energy Group, Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Michiel Zaaijer
Wind Energy Group, Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Dominic von Terzi
Wind Energy Group, Faculty of Aerospace Engineering, Delft University of Technology, Delft, the Netherlands
Related authors
Mihir Kishore Mehta, Michiel Zaaijer, and Dominic von Terzi
Wind Energ. Sci., 9, 2283–2300, https://doi.org/10.5194/wes-9-2283-2024, https://doi.org/10.5194/wes-9-2283-2024, 2024
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In a subsidy-free era, there is a need to optimize wind turbines for maximizing farm revenue instead of minimizing cost of energy. A wind-farm-level modeling framework with a simplified market model is used to optimize the turbine size for maximum profitability. The results show that the optimum size is driven mainly by the choice of the economic metric and the market price scenario, with a design optimized for the cost of energy already performing well w.r.t. most profitability-based metrics
Nils Barfknecht and Dominic von Terzi
Wind Energ. Sci., 9, 2333–2357, https://doi.org/10.5194/wes-9-2333-2024, https://doi.org/10.5194/wes-9-2333-2024, 2024
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Rain droplets damage wind turbine blades due to the high impact speed at the tip. In this study, it is found that rain droplets and wind turbine blades interact aerodynamically. The rain droplets slow down and deform close to the blade. A model from another field of study was adapted and validated to study this process in detail. This effect reduced the predicted erosion damage by up to 50 %, primarily affecting smaller drops. It is shown how the slowdown effect can influence erosion mitigation.
Mihir Kishore Mehta, Michiel Zaaijer, and Dominic von Terzi
Wind Energ. Sci., 9, 2283–2300, https://doi.org/10.5194/wes-9-2283-2024, https://doi.org/10.5194/wes-9-2283-2024, 2024
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In a subsidy-free era, there is a need to optimize wind turbines for maximizing farm revenue instead of minimizing cost of energy. A wind-farm-level modeling framework with a simplified market model is used to optimize the turbine size for maximum profitability. The results show that the optimum size is driven mainly by the choice of the economic metric and the market price scenario, with a design optimized for the cost of energy already performing well w.r.t. most profitability-based metrics
Rishikesh Joshi, Dominic von Terzi, and Roland Schmehl
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-161, https://doi.org/10.5194/wes-2024-161, 2024
Preprint under review for WES
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This paper presents a methodology for system design of airborne wind energy (AWE). A multi-disciplinary design, analysis, and optimization (MDAO) framework was developed, integrating power, energy production, and cost models for fixed-wing ground-generation (GG) AWE systems. Using the levelized cost of electricity (LCoE) as the design objective, we found that the optimal size of systems lies between the rated power of 100 kW and 1000 kW.
Shyam VimalKumar, Delphine De Tavernier, Dominic von Terzi, Marco Belloli, and Axelle Viré
Wind Energ. Sci., 9, 1967–1983, https://doi.org/10.5194/wes-9-1967-2024, https://doi.org/10.5194/wes-9-1967-2024, 2024
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When standing still without a nacelle or blades, the vibrations on a wind turbine tower are of concern to its structural health. This study finds that the air which flows around the tower recirculates behind the tower, forming so-called wakes. These wakes initiate the vibration, and the movement itself causes the vibration to increase or decrease depending on the wind speed. The current study uses a methodology called force partitioning to analyse this in depth.
Maria Cristina Vitulano, Delphine Anne Marie De Tavernier, Giuliano De Stefano, and Dominic Alexander von Terzi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-47, https://doi.org/10.5194/wes-2024-47, 2024
Revised manuscript accepted for WES
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Next-generation wind turbines are the largest rotating machines ever built, experiencing local flow Mach where the incompressibility assumption is violated, and even transonic flow can occur. This study assesses the transonic features over the FFA-W3-211 wind turbine tip airfoil for selected industrial test cases, defines the subsonic-supersonic flow threshold, and evaluates the Reynolds number effects on transonic flow occurrence. Shock wave occurrence is also depicted.
Nils Barfknecht and Dominic von Terzi
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2024-33, https://doi.org/10.5194/wes-2024-33, 2024
Revised manuscript accepted for WES
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The paper investigates the influence of the rain drop diameter on the formation of erosion damage and its implication for the erosion-safe mode (ESM). By building an erosion damage model that incorporates several drop-size effects, it is found that large droplets are significantly more erosive than small droplets. It is shown that the performance of the ESM is significantly increased when drop-size effects are correctly accounted for. A method to derive optimal ESM strategies is given as well.
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.
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.
Erik Quaeghebeur and Michiel B. Zaaijer
Wind Energ. Sci., 5, 285–308, https://doi.org/10.5194/wes-5-285-2020, https://doi.org/10.5194/wes-5-285-2020, 2020
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Meteorological and oceanic datasets are fundamental to the modeling of offshore wind farms. Data quality issues in one such dataset led us to conduct a study to establish whether such issues are more generally present in these datasets. The answer is yes and users should be aware of this. We therefore also investigated how such issues can be avoided. The result is a set of techniques and recommendations for dataset producers, leading to substantial quality improvements with limited extra effort.
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.
Related subject area
Thematic area: Wind technologies | Topic: Systems engineering
Designing wind turbines for profitability in the day-ahead market
Aerodynamic effects of leading-edge erosion in wind farm flow modeling
Control co-design optimization of floating offshore wind turbines with tuned liquid multi-column dampers
Knowledge engineering for wind energy
HyDesign: a tool for sizing optimization of grid-connected hybrid power plants including wind, solar photovoltaic, and lithium-ion batteries
The eco-conscious wind turbine: design beyond purely economic metrics
A comparison of eight optimization methods applied to a wind farm layout optimization problem
Optimization of wind farm operation with a noise constraint
Flutter behavior of highly flexible blades for two- and three-bladed wind turbines
Mihir Kishore Mehta, Michiel Zaaijer, and Dominic von Terzi
Wind Energ. Sci., 9, 2283–2300, https://doi.org/10.5194/wes-9-2283-2024, https://doi.org/10.5194/wes-9-2283-2024, 2024
Short summary
Short summary
In a subsidy-free era, there is a need to optimize wind turbines for maximizing farm revenue instead of minimizing cost of energy. A wind-farm-level modeling framework with a simplified market model is used to optimize the turbine size for maximum profitability. The results show that the optimum size is driven mainly by the choice of the economic metric and the market price scenario, with a design optimized for the cost of energy already performing well w.r.t. most profitability-based metrics
Jens Visbech, Tuhfe Göçmen, Özge Sinem Özçakmak, Alexander Meyer Forsting, Ásta Hannesdóttir, and Pierre-Elouan Réthoré
Wind Energ. Sci., 9, 1811–1826, https://doi.org/10.5194/wes-9-1811-2024, https://doi.org/10.5194/wes-9-1811-2024, 2024
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Leading-edge erosion (LEE) can impact wind turbine aerodynamics and wind farm efficiency. This study couples LEE prediction, aerodynamic loss modeling, and wind farm flow modeling to show that LEE's effects on wake dynamics can affect overall energy production. Without preventive initiatives, the effects of LEE increase over time, resulting in significant annual energy production (AEP) loss.
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.
Yuriy Marykovskiy, Thomas Clark, Justin Day, Marcus Wiens, Charles Henderson, Julian Quick, Imad Abdallah, Anna Maria Sempreviva, Jean-Paul Calbimonte, Eleni Chatzi, and Sarah Barber
Wind Energ. Sci., 9, 883–917, https://doi.org/10.5194/wes-9-883-2024, https://doi.org/10.5194/wes-9-883-2024, 2024
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This paper delves into the crucial task of transforming raw data into actionable knowledge which can be used by advanced artificial intelligence systems – a challenge that spans various domains, industries, and scientific fields amid their digital transformation journey. This article underscores the significance of cross-industry collaboration and learning, drawing insights from sectors leading in digitalisation, and provides strategic guidance for further development in this area.
Juan Pablo Murcia Leon, Hajar Habbou, Mikkel Friis-Møller, Megha Gupta, Rujie Zhu, and Kaushik Das
Wind Energ. Sci., 9, 759–776, https://doi.org/10.5194/wes-9-759-2024, https://doi.org/10.5194/wes-9-759-2024, 2024
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A methodology for an early design of hybrid power plants (wind, solar, PV, and Li-ion battery storage) consisting of a nested optimization that sizes the components and internal operation optimization. Traditional designs that minimize the levelized cost of energy give worse business cases and do not include storage. Optimal operation balances the increasing revenues and faster battery degradation. Battery degradation and replacement costs are needed to estimate the viability of hybrid projects.
Helena Canet, Adrien Guilloré, and Carlo L. Bottasso
Wind Energ. Sci., 8, 1029–1047, https://doi.org/10.5194/wes-8-1029-2023, https://doi.org/10.5194/wes-8-1029-2023, 2023
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We propose a new approach to design that aims at optimal trade-offs between economic and environmental goals. New environmental metrics are defined, which quantify impacts in terms of CO2-equivalent emissions produced by the turbine over its entire life cycle. For some typical onshore installations in Germany, results indicate that a 1 % increase in the cost of energy can buy about a 5 % decrease in environmental impacts: a small loss for the individual can lead to larger gains for society.
Jared J. Thomas, Nicholas F. Baker, Paul Malisani, Erik Quaeghebeur, Sebastian Sanchez Perez-Moreno, John Jasa, Christopher Bay, Federico Tilli, David Bieniek, Nick Robinson, Andrew P. J. Stanley, Wesley Holt, and Andrew Ning
Wind Energ. Sci., 8, 865–891, https://doi.org/10.5194/wes-8-865-2023, https://doi.org/10.5194/wes-8-865-2023, 2023
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This work compares eight optimization algorithms (including gradient-based, gradient-free, and hybrid) on a wind farm optimization problem with 4 discrete regions, concave boundaries, and 81 wind turbines. Algorithms were each run by researchers experienced with that algorithm. Optimized layouts were unique but with similar annual energy production. Common characteristics included tightly-spaced turbines on the outer perimeter and turbines loosely spaced and roughly on a grid in the interior.
Camilla Marie Nyborg, Andreas Fischer, Pierre-Elouan Réthoré, and Ju Feng
Wind Energ. Sci., 8, 255–276, https://doi.org/10.5194/wes-8-255-2023, https://doi.org/10.5194/wes-8-255-2023, 2023
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Our article presents a way of optimizing the wind farm operation by keeping the emitted noise level below a defined limit while maximizing the power output. This is done by switching between noise reducing operational modes. The method has been developed by using two different noise models, one more advanced than the other, to study the advantages of each model. Furthermore, the optimization method is applied to different wind farm cases.
Mayank Chetan, Shulong Yao, and D. Todd Griffith
Wind Energ. Sci., 7, 1731–1751, https://doi.org/10.5194/wes-7-1731-2022, https://doi.org/10.5194/wes-7-1731-2022, 2022
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Though large wind turbines are appealing to reduce costs, larger blades are prone to aero-elastic instabilities due to their long, slender, highly flexible nature. New rotor concepts are emerging including two-bladed rotors and downwind configurations. We introduce a comprehensive evaluation of flutter behavior including classical flutter and edgewise vibration for large-scale two-bladed rotors. The study aims to provide designers with insights to mitigate flutter in future designs.
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Short summary
Turbines are becoming larger. However, it is important to understand the key drivers of turbine design and explore the possibility of a global optimum, beyond which further upscaling might not reduce the cost of energy. This study explores, for a typical farm, the entire turbine design space with respect to rated power and rotor diameter. The results show a global optimum that is subject to various modeling uncertainties, farm design conditions, and policies with respect to wind farm tendering.
Turbines are becoming larger. However, it is important to understand the key drivers of turbine...
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