@misc{11cdd29c31394d759285537946838f2a,
title = "Effects of Changing Atmospheric Conditions on Wind Turbine Performance (Poster)",
abstract = "Multi-megawatt, utility-scale wind turbines operate in turbulent and dynamic winds that impact turbine performance in ways that are gradually becoming better understood. This poster presents a study made using a turbulent flow field simulator (TurbSim) and a Turbine aeroelastic simulator (FAST) of the response of a generic 1.5 MW wind turbine to changing inflow. The turbine power output is foundto be most sensitive to wind speed and turbulence intensity, but the relationship depends on the wind speed with respect to the turbine's rated wind speed. Shear is found to be poorly correlated to power. A machine learning method called 'regression trees' is used to create a simple model of turbine performance that could be used as part of the wind resource assessment process. This study hasused simple flow fields and should be extended to more complex flows, and validated with field observations.",
keywords = "annualized energy production, loads, prediction, turbulence, wind resource assessment, wind turbine",
author = "Andrew Clifton and Paul Fleming and Levi Kilcher and Julie Lundquist",
year = "2012",
language = "American English",
series = "Presented at the American Geophysical Union Fall Meeting, 3-7 December 2012, San Francisco, California",
publisher = "National Renewable Energy Laboratory (NREL)",
address = "United States",
type = "Other",
}