Fatigue design load calculations of the offshore NREL 5MW benchmark turbine using quadrature rule techniques
For wind turbine designers, this method reduces computational cost of fatigue load calculations while maintaining accuracy, though it is an incremental improvement over binning.
The paper proposes a quadrature rule-based approach to reduce the number of aeroelastic code evaluations needed for fatigue load calculations on offshore wind turbines, achieving accurate equivalent load estimations with significantly fewer evaluations compared to conventional binning. The method is demonstrated on the NREL 5MW turbine using North Sea data, showing computational time reduction.
A novel approach is proposed to reduce, compared to the conventional binning approach, the large number of aeroelastic code evaluations that are necessary to obtain equivalent loads acting on wind turbines. These loads describe the effect of long-term environmental variability on the fatigue loads of a horizontal-axis wind turbine. In particular Design Load Case 1.2, as standardized by IEC, is considered. The approach is based on numerical integration techniques and, more specifically, quadrature rules. The quadrature rule used in this work is a recently proposed "implicit" quadrature rule, which has the main advantage that it can be constructed directly using measurements of the environment. It is demonstrated that the proposed approach yields accurate estimations of the equivalent loads using a significantly reduced number of aeroelastic model evaluations (compared to binning). Moreover the error introduced by the seeds (introduced by averaging over random wind fields and sea states) is incorporated in the quadrature framework, yielding an even further reduction in the number of aeroelastic code evaluations. The reduction in computational time is demonstrated by assessing the fatigue loads on the NREL 5MW reference offshore wind turbine in conjunction with measurement data obtained at the North Sea, both for a simplified and a full load case.