Probabilistic Design Methods for Gust-Based Loads on Wind Turbines

• Published in: Energies (Basel) Vol. 17; no. 7; p. 1518
• Main Authors: Abhinav, K. A., Sørensen, John D., Hammerum, Keld, Nielsen, Jannie S.
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2024
• Subjects: Air-turbines; Analysis; Capital expenditures; Design techniques; Environmental conditions; extreme load; Methods; Offshore; probabilistic design; Simulation; Simulation methods; structural reliability analysis; Turbine industry; Turbines; Turbulence models; Wind farms; Iran; Denmark; United States
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en17071518

The IEC 61400-1 standard specifies design load cases (DLCs) to be considered in the design of wind turbine structures. Specifically, DLC 2.3 considers the occurrence of a gust while the turbine shuts down due to an electrical fault. Originally, this load case used a deterministic wind event called the extreme operating gust (EOG), but the standard now also includes an approach for calculating the extreme response based on stochastic simulations with turbulent wind. This study presents and compares existing approaches with novel probabilistic design approaches for DLC 2.3 based on simulations with turbulent wind. First, a semiprobabilistic approach is proposed, where the inverse first-order reliability method (iFORM) is used for the extrapolation of the response for electrical faults occurring at a given rate. Next, three probabilistic approaches are formulated for the calculation of the reliability index, which differs in how the aggregation is performed over wind conditions and whether faults are modeled using a Poisson distribution or just by the rate. An example illustrates the methods considering the tower fore-aft bending moment at the tower base and shows that the approach based on iFORM can lead to reductions in material usage compared to the existing methods. For reliability assessment, the probabilistic approach using the Poisson process is needed for high failure rates, and the reliabilities obtained for designs using all semiprobabilistic methods are above the target level, indicating that further reductions may be obtained via the use of probabilistic design methods.