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Title: Uncertainty propagation through an aeroelastic wind turbine model using polynomial surrogates

Abstract

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 miss-alignment. 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 work-flows 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:
ORCiD logo [1];  [1];  [1];  [1];  [2];  [3];  [1]
  1. Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy
  2. Technical Univ. of Denmark, Roskilde (Denmark). Dept. of Wind Energy; Aalborg Univ., Aalborg (Denmark)
  3. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
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)
OSTI Identifier:
1411128
Report Number(s):
NREL/JA-2C00-70570
Journal ID: ISSN 0960-1481
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Renewable Energy
Additional Journal Information:
Journal Volume: 119; Journal Issue: C; Journal ID: ISSN 0960-1481
Publisher:
Elsevier
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

Citation Formats

Murcia, Juan Pablo, Réthoré, Pierre-Elouan, 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., 2017. Web. doi:10.1016/j.renene.2017.07.070.
Murcia, Juan Pablo, Réthoré, Pierre-Elouan, 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, Pierre-Elouan, Dimitrov, Nikolay, Natarajan, Anand, Sørensen, John Dalsgaard, Graf, Peter, and Kim, Taeseong. Mon . "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, Pierre-Elouan 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 miss-alignment. 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 work-flows 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 = {Mon Jul 17 00:00:00 EDT 2017},
month = {Mon Jul 17 00:00:00 EDT 2017}
}

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