TY - GEN
T1 - Stochastic optimization of a horizontal-axis composite wind turbine blade
AU - Thapa, Mishal
AU - Missoum, Samy
N1 - Funding Information:
The support of the Arizona Board of Regents and Arizona State University through a Regent’s Innovation Fund (Grant ASUB00000374) is gratefully acknowledged.
Publisher Copyright:
Copyright © 2020 ASME
PY - 2020
Y1 - 2020
N2 - In this paper, the stochastic optimization of a horizontalaxis composite wind turbine blade is performed. Wind energy has become widely popular in recent decades as an alternative source of energy and many studies have been devoted to finding an optimal wind turbine blade using deterministic optimization. However, the actual responses of the wind turbine blade such as power generation are affected by the stochastic nature of wind, uncertainties in material properties and modeling parameters, and so on. This can have an undesirable impact on the performance and reliability of blades, which demands the consideration of uncertainties during optimization. To this end, a surrogate-based stochastic optimization of a wind turbine blade considering the influence of randomness in wind speed on power generation was studied. A slight gain in average power over the baseline blade was obtained and it demonstrated the promise of the presented framework for the design of wind turbine blades.
AB - In this paper, the stochastic optimization of a horizontalaxis composite wind turbine blade is performed. Wind energy has become widely popular in recent decades as an alternative source of energy and many studies have been devoted to finding an optimal wind turbine blade using deterministic optimization. However, the actual responses of the wind turbine blade such as power generation are affected by the stochastic nature of wind, uncertainties in material properties and modeling parameters, and so on. This can have an undesirable impact on the performance and reliability of blades, which demands the consideration of uncertainties during optimization. To this end, a surrogate-based stochastic optimization of a wind turbine blade considering the influence of randomness in wind speed on power generation was studied. A slight gain in average power over the baseline blade was obtained and it demonstrated the promise of the presented framework for the design of wind turbine blades.
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U2 - 10.1115/IMECE2020-24004
DO - 10.1115/IMECE2020-24004
M3 - Conference contribution
AN - SCOPUS:85097257194
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Safety Engineering, Risk, and Reliability Analysis
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
Y2 - 16 November 2020 through 19 November 2020
ER -