Abstract
Abstract. A new method is described to identify the aerodynamic characteristics of blade airfoils directly from operational data of the turbine. Improving on a previously published approach, the present method is based on a new maximum likelihood formulation that includes errors in both the outputs and the inputs, generalizing the classical error-in-the-outputs-only formulation. Since many parameters are necessary to meaningfully represent the behavior of airfoil polars as functions of angle of attack and Reynolds number, the approach uses a singular value decomposition to solve for a reduced set of observable parameters. The new method is demonstrated by identifying high-quality polars for small-scale wind turbines used in wind tunnel experiments for wake and wind farm control research.
Highlights
Most simulation models of wind turbine rotors, from the low to the high end of the fidelity spectrum, rely on polars, i.e., on the aerodynamic characteristics of the airfoils used on the blade
Airfoil polars are used for modeling the aerodynamics of rotors using lifting lines in conjunction with blade element momentum (BEM), free vortex wake (FVW), and computational fluid dynamic (CFD) models
Using the method of Bottasso et al (2014a), the nominal airfoil polars are augmented with parametric correction terms, which are identified using a maximum likelihood (ML) criterion based on operational power and thrust measurements
Summary
Most simulation models of wind turbine rotors, from the low to the high end of the fidelity spectrum, rely on polars, i.e., on the aerodynamic characteristics of the airfoils used on the blade. Using the method of Bottasso et al (2014a), the nominal airfoil polars are augmented with parametric correction terms, which are identified using a maximum likelihood (ML) criterion based on operational power and thrust measurements These data points are collected on the turbine at various operating conditions, selected in order to span a desired range of angles of attack and Reynolds numbers. Inputs represent the operating conditions of the turbines, which are expressed by the ambient air density and wind speed, the rotor angular velocity, and the blade pitch setting Errors in such quantities have a non-negligible effect on the outputs and should be taken into account in a rigorous statistical sense.
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