Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

National Wind Technology Center

Research output: NREL › Fact Sheet

Abstract

The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

Original language	American English
Number of pages	2
State	Published - 2022

NREL Publication Number

NREL/FS-5000-82756

Keywords

aerodynamics
airfoil
blade
inverse design
machine learning
neural networks
wind energy

Access to Document

https://www.nrel.gov/docs/fy22osti/82756.pdf

Cite this

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title = "Enabling Innovation in Wind Turbine Design Using Artificial Intelligence",

abstract = "The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.",

keywords = "aerodynamics, airfoil, blade, inverse design, machine learning, neural networks, wind energy",

author = "NREL",

year = "2022",

language = "American English",

type = "Other",

}

TY - GEN

T1 - Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

AU - NREL, null

PY - 2022

Y1 - 2022

N2 - The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

AB - The Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements (INTEGRATE) project is developing a new inverse-design capability for wind turbine rotors using invertible neural networks. This artificial intelligence (AI)-based technology can capture complex nonlinear aerodynamic effects 100 times faster than alternative design approaches.

KW - aerodynamics

KW - airfoil

KW - blade

KW - inverse design

KW - machine learning

KW - neural networks

KW - wind energy

M3 - Fact Sheet

ER -

Enabling Innovation in Wind Turbine Design Using Artificial Intelligence

Abstract

NREL Publication Number

Keywords

Access to Document

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Cite this