Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates
Polynomial surrogates are used to characterize the energy production and lifetime equivalent fatigue loads for different components of the DTU 10 MW reference wind turbine under realistic atmospheric conditions. The variability caused by different turbulent inflow fields are captured by creating independent surrogates for the mean and standard deviation of each output with respect to the inflow realizations. A global sensitivity analysis shows that the turbulent inflow realization has a bigger impact on the total distribution of equivalent fatigue loads than the shear coefficient or yaw missalignment. The methodology presented extends the deterministic power and thrust coefficient curves to uncertainty models and adds new variables like damage equivalent fatigue loads in different components of the turbine. These surrogate models can then be implemented inside other workflows such as: estimation of the uncertainty in annual energy production due to wind resource variability and/or robust wind power plant layout optimization. It can be concluded that it is possible to capture the global behavior of a modern wind turbine and its uncertainty under realistic inflow conditions using polynomial response surfaces. In conclusion, the surrogates are a way to obtain power and load estimation under site specific characteristics without sharing the proprietary aeroelastic design.
 Authors:

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 Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy
 Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy; Aalborg Univ., Aalborg (Denmark)
 National Renewable Energy Lab. (NREL), Golden, CO (United States)
 Publication Date:
 Report Number(s):
 NREL/JA2C0070570
Journal ID: ISSN 09601481
 Grant/Contract Number:
 AC3608GO28308
 Type:
 Accepted Manuscript
 Journal Name:
 Renewable Energy
 Additional Journal Information:
 Journal Volume: 119; Journal Issue: C; Journal ID: ISSN 09601481
 Publisher:
 Elsevier
 Research Org:
 National Renewable Energy Lab. (NREL), Golden, CO (United States)
 Sponsoring Org:
 USDOE Office of Energy Efficiency and Renewable Energy (EERE); Korea Institute of Energy Technology Evaluation and Planning (KETEP)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 17 WIND ENERGY; wind energy; uncertainty quantification; aeroelastic wind turbine model; annual energy production; lifetime equivalent fatigue loads
 OSTI Identifier:
 1411128
Murcia, Juan Pablo, Réthoré, PierreElouan, Dimitrov, Nikolay, Natarajan, Anand, Sørensen, John Dalsgaard, Graf, Peter, and Kim, Taeseong. Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates. United States: N. p.,
Web. doi:10.1016/j.renene.2017.07.070.
Murcia, Juan Pablo, Réthoré, PierreElouan, Dimitrov, Nikolay, Natarajan, Anand, Sørensen, John Dalsgaard, Graf, Peter, & Kim, Taeseong. Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates. United States. doi:10.1016/j.renene.2017.07.070.
Murcia, Juan Pablo, Réthoré, PierreElouan, Dimitrov, Nikolay, Natarajan, Anand, Sørensen, John Dalsgaard, Graf, Peter, and Kim, Taeseong. 2017.
"Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates". United States.
doi:10.1016/j.renene.2017.07.070. https://www.osti.gov/servlets/purl/1411128.
@article{osti_1411128,
title = {Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates},
author = {Murcia, Juan Pablo and Réthoré, PierreElouan and Dimitrov, Nikolay and Natarajan, Anand and Sørensen, John Dalsgaard and Graf, Peter and Kim, Taeseong},
abstractNote = {Polynomial surrogates are used to characterize the energy production and lifetime equivalent fatigue loads for different components of the DTU 10 MW reference wind turbine under realistic atmospheric conditions. The variability caused by different turbulent inflow fields are captured by creating independent surrogates for the mean and standard deviation of each output with respect to the inflow realizations. A global sensitivity analysis shows that the turbulent inflow realization has a bigger impact on the total distribution of equivalent fatigue loads than the shear coefficient or yaw missalignment. The methodology presented extends the deterministic power and thrust coefficient curves to uncertainty models and adds new variables like damage equivalent fatigue loads in different components of the turbine. These surrogate models can then be implemented inside other workflows such as: estimation of the uncertainty in annual energy production due to wind resource variability and/or robust wind power plant layout optimization. It can be concluded that it is possible to capture the global behavior of a modern wind turbine and its uncertainty under realistic inflow conditions using polynomial response surfaces. In conclusion, the surrogates are a way to obtain power and load estimation under site specific characteristics without sharing the proprietary aeroelastic design.},
doi = {10.1016/j.renene.2017.07.070},
journal = {Renewable Energy},
number = C,
volume = 119,
place = {United States},
year = {2017},
month = {7}
}