To harvest more energy from wind, wind turbine size has rapidly increased, entailing the serious concern on the reliability of the wind turbine. Accordingly, the international standard requires turbine designers to estimate the extreme load that could be imposed on a turbine during normal operations. At the design stage, physics-based load simulations can be used for this purpose. However, simulating the extreme load associated with a small load exceedance probability is computationally prohibitive. In this study, we propose using importance sampling combined with order statistics to reduce the computational burden significantly while achieving much better estimation accuracy than existing methods.
Computationally Efficient Uncertainty Minimization in Wind Turbine Extreme Load Assessments
Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received May 21, 2015; final manuscript received April 27, 2016; published online June 14, 2016. Assoc. Editor: Yves Gagnon.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Choe, Y., Pan, Q., and Byon, E. (June 14, 2016). "Computationally Efficient Uncertainty Minimization in Wind Turbine Extreme Load Assessments." ASME. J. Sol. Energy Eng. August 2016; 138(4): 041012. https://doi.org/10.1115/1.4033511
Download citation file:
- Ris (Zotero)
- Reference Manager