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Title: Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches

Abstract

A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the input parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into themore » already powerful importance sampling concept.« less

Authors:
; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1357742
Report Number(s):
NREL/CP-2C00-67470
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the AIAA SciTech Forum: 35th Wind Energy Symposium, 9-13 January 2017, Grapevine, Texas
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind turbines; load calculation; extreme load

Citation Formats

Graf, Peter, Damiani, Rick R., Dykes, Katherine, and Jonkman, Jason M. Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches. United States: N. p., 2017. Web. doi:10.2514/6.2017-0680.
Graf, Peter, Damiani, Rick R., Dykes, Katherine, & Jonkman, Jason M. Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches. United States. doi:10.2514/6.2017-0680.
Graf, Peter, Damiani, Rick R., Dykes, Katherine, and Jonkman, Jason M. Mon . "Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches". United States. doi:10.2514/6.2017-0680.
@article{osti_1357742,
title = {Advances in the Assessment of Wind Turbine Operating Extreme Loads via More Efficient Calculation Approaches},
author = {Graf, Peter and Damiani, Rick R. and Dykes, Katherine and Jonkman, Jason M.},
abstractNote = {A new adaptive stratified importance sampling (ASIS) method is proposed as an alternative approach for the calculation of the 50 year extreme load under operational conditions, as in design load case 1.1 of the the International Electrotechnical Commission design standard. ASIS combines elements of the binning and extrapolation technique, currently described by the standard, and of the importance sampling (IS) method to estimate load probability of exceedances (POEs). Whereas a Monte Carlo (MC) approach would lead to the sought level of POE with a daunting number of simulations, IS-based techniques are promising as they target the sampling of the input parameters on the parts of the distributions that are most responsible for the extreme loads, thus reducing the number of runs required. We compared the various methods on select load channels as output from FAST, an aero-hydro-servo-elastic tool for the design and analysis of wind turbines developed by the National Renewable Energy Laboratory (NREL). Our newly devised method, although still in its infancy in terms of tuning of the subparameters, is comparable to the others in terms of load estimation and its variance versus computational cost, and offers great promise going forward due to the incorporation of adaptivity into the already powerful importance sampling concept.},
doi = {10.2514/6.2017-0680},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 09 00:00:00 EST 2017},
month = {Mon Jan 09 00:00:00 EST 2017}
}

Conference:
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