Articles | Volume 9, issue 10
https://doi.org/10.5194/wes-9-2017-2024
© 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-9-2017-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Oct 2024
Research article |
| 29 Oct 2024
| 29 Oct 2024
Full-scale wind turbine performance assessment using the turbine performance integral (TPI) method: a study of aerodynamic degradation and operational influences
Vattenfall, Amerigo-Vespucci-Platz 2, 20457, Hamburg, Germany
Christian Bak
Department of Wind and Energy Systems, Technical University of Denmark, Roskilde, Denmark
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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 under review 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
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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.
Tahir H. Malik and Christian Bak
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Revised manuscript under review 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
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Preprint under review for WES
Short summary
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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
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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, and Michael McWilliam
Wind Energ. Sci., 6, 917–933, https://doi.org/10.5194/wes-6-917-2021, https://doi.org/10.5194/wes-6-917-2021, 2021
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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.
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.
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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.
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We collate the latest reliability data in operations and maintenance (O&M) for offshore wind turbines, specifically large turbines of 15 MW. We use these data to model O&M of an offshore wind farm at three different sites. We compare two industry-dominant drivetrain configurations in terms of O&M cost for 15 MW turbines and determine if previous results for smaller turbines still hold true. Comparisons between drivetrains are topical within industry, and we produce cost comparisons for them.
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Rafael Abreu, Daniel Peter, and Christine Thomas
Wind Energ. Sci., 7, 1227–1239, https://doi.org/10.5194/wes-7-1227-2022, https://doi.org/10.5194/wes-7-1227-2022, 2022
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Clemens Jonscher, Benedikt Hofmeister, Tanja Grießmann, and Raimund Rolfes
Wind Energ. Sci., 7, 1053–1067, https://doi.org/10.5194/wes-7-1053-2022, https://doi.org/10.5194/wes-7-1053-2022, 2022
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Short summary
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.
We explore the effect of blade modifications on offshore wind turbines' performance through a...
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