Articles | Volume 9, issue 12
https://doi.org/10.5194/wes-9-2283-2024
© 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-9-2283-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Dec 2024
Research article |
| 05 Dec 2024
| 05 Dec 2024
Designing wind turbines for profitability in the day-ahead market
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
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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
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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.
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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
In a subsidy-free era, there is a need to optimize wind turbines for maximizing farm revenue...
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