From wind to loads: wind turbine site-specific load estimation using databases with high-fidelity load simulations

Abstract. We define and demonstrate a procedure for quick assessment of site-specific lifetime fatigue loads, using surrogate models calibrated by means of a database with high-fidelity load simulations. The performance of six surrogate models is assessed by comparing site-specific lifetime fatigue load predictions at ten sites. The surrogate methods include polynomial-chaos expansion, quadratic response surface, universal Kriging, importance sampling, and nearest-neighbor interpolation. Practical bounds for the database and calibration are defined via nine environmental variables, and their relative effects on the fatigue loads are evaluated by means of Sobol sensitivity indices. Of the surrogate-model methods, polynomial-chaos expansion provided an accurate and robust performance in prediction of the different site-specific loads. Although the Kriging approach showed slightly better accuracy, it also demanded more computational resources. Taking into account other useful properties of the polynomial chaos expansion method within the performance comparisons, we consider it to generally be the most useful for quick assessment of site-specific loads.