Beyond wind-sector management: optimal wind farm operational planning for balancing fatigue damage and extending lifetime

Abstract. We present an optimization framework for long‑term wind farm operation that balances fatigue loads and energy yield to extend turbine and farm lifetime. The approach plans per‑turbine derating setpoints for discrete wind conditions using an engineering wake model and surrogate models for power and damage. We formulate the problem as a nonlinear program and solve it either for the full farm in a single run or iteratively per turbine. The method is demonstrated on a 9‑turbine farm under onshore and offshore turbulence conditions and across multiple failure modes. For tower bottom bending, modest lifetime extensions of 2–5 years increase net present value (NPV) between (5 % and more than 100 %) with small losses of annual energy production (AEP) of 1–4 % onshore and less than 0.2 % offshore. The per‑turbine optimization achieves similar results as the full farm approach in most cases. Under offshore turbulence, upstream derating more effectively reduces wake‑induced turbulence and the coordinated farm optimization yields additional benefits. When blade edgewise loads are included, lifetime gains require stronger derating due to rotational‑speed sensitivity and reduce economic benefits. The framework produces implementable lookup tables that can be integrated into wind farm planning and control. While results rely on steady wake models and design‑style damage estimation and thus represent first‑order comparisons, they show that targeted derating can redistribute damage and extend lifetime with limited impact on energy.

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Publication Details

Journal
Wind energy science
Published
2026-10-15
DOI
https://doi.org/10.5194/wes-11-3863-2026
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
0.00

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article

Beyond wind-sector management: optimal wind farm operational planning for balancing fatigue damage and extending lifetime

René Hofmann, Niklas Requate, Lukas Vollmer
Wind energy science
Wind Energy Research and Development
article

Beyond wind-sector management: optimal wind farm operational planning for balancing fatigue damage and extending lifetime

René Hofmann, Niklas Requate, Lukas Vollmer
article en

Abstract

Abstract. We present an optimization framework for long‑term wind farm operation that balances fatigue loads and energy yield to extend turbine and farm lifetime. The approach plans per‑turbine derating setpoints for discrete wind conditions using an engineering wake model and surrogate models for power and damage. We formulate the problem as a nonlinear program and solve it either for the full farm in a single run or iteratively per turbine. The method is demonstrated on a 9‑turbine farm under onshore and offshore turbulence conditions and across multiple failure modes. For tower bottom bending, modest lifetime extensions of 2–5 years increase net present value (NPV) between (5 % and more than 100 %) with small losses of annual energy production (AEP) of 1–4 % onshore and less than 0.2 % offshore. The per‑turbine optimization achieves similar results as the full farm approach in most cases. Under offshore turbulence, upstream derating more effectively reduces wake‑induced turbulence and the coordinated farm optimization yields additional benefits. When blade edgewise loads are included, lifetime gains require stronger derating due to rotational‑speed sensitivity and reduce economic benefits. The framework produces implementable lookup tables that can be integrated into wind farm planning and control. While results rely on steady wake models and design‑style damage estimation and thus represent first‑order comparisons, they show that targeted derating can redistribute damage and extend lifetime with limited impact on energy.

Wind energy scienceVol. 11(10)
TU Wien (AT), Fraunhofer Institute for Wind Energy Systems (DE)
Bundesministerium für Wirtschaft und Energie
Affordable and clean energy, Climate action
Openalex Percentile: Top 99%
Wind Energy Research and Development
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