Temporal Coherence Importance Sampling for Wind Turbine Extreme Loads Estimation
Estimating long return period extreme wind turbine loads is made especially difficult by the large response variability for 'the same' environmental conditions. To alleviate this, we have 'opened up the black box' of the turbulent wind generation stage of the simulations. Exploiting the notion of 'temporal coherence' allows us to manipulate the turbulent inflow to target extreme wind conditions, while at the same time quantifying 'how probable these are.' The resulting importance sampling load estimates achieve a significantly lower exceedance probability (i.e., they represent much longer return periods) than estimates using the same number of samples (i.e., the same computational resources) but only a standard Monte Carlo estimate.
- Research Organization:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1547232
- Report Number(s):
- NREL/CP-2C00-72692
- Resource Relation:
- Conference: Presented at the AIAA SciTech 2019 Forum, 7-11 January 2019, San Diego, California
- Country of Publication:
- United States
- Language:
- English
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