Abstract
This study addresses the feasibility of modeling wind-farm wake-turbulence autospectra and coherences from a database: flow velocity points from experimental and computational fluid dynamics (CFD) investigations. Specifically, it first applies an earlier-exercised framework to construct the autospectral models from a database and then it adopts a recently proposed framework to construct the coherence models from a database. While this proposed framework has not been tested against a database, the methodology has been completely formulated with a theoretical basis. These models of autospectrum and coherence are interpretive, and in closed form. Both frameworks basically involve the perturbation series expansion of the autospectra and coherences. The framework for modeling autospectra is tested against a demanding database of wake turbulence inside a wind farm over a complex terrain from a full-scale test. The suitability of these autospectral models for simulation through white-noise driven filters is also demonstrated. Finally, coherence models are generated for assumed values of the perturbation series constants, and these coherence models are used to demonstrate how the coherence models of homogeneous isotropic turbulence deviate from the coherence models of non-homogeneous non-isotropic turbulence such as wind-farm wake turbulence. This feasibility of extracting both the one-point statistics of autospectral models and the two-point statistics of coherence models from a database represents a research avenue that is new and promising in the treatment of wind-farm wake turbulence. This paper also demonstrates the feasibility of fruitfully exploiting the wake treatment methods developed in other fields.
Highlights
During the past thirty years, wake turbulence and its effects on wind turbines and wind farms have been extensively investigated, primarily analytically and to some extent experimentally
For wake-turbulence modeling from the low-fidelity computational fluid dynamics (CFD) treatment of the Navier-Stokes (NS) equations, and Carrion et al [3] for wake-turbulence modeling from the high-fidelity treatment of NS equations
A comparison of the measured autospectra of ambient atmospheric boundary layer turbulence dimensionless frequency f z/U, where z is the mast height and U is the mean wind speed. These (ABL) and wake turbulence shows that the ABL autospectrum has gone through changes in energy autospectra were experimentally generated theshould samehelp location a wind farm over distribution with respect to frequency
Summary
During the past thirty years, wake turbulence and its effects on wind turbines and wind farms have been extensively investigated, primarily analytically and to some extent experimentally. The recent study due to Krishnan and Gaonkar [8] follows this second approach; not tested against a database, the framework is formulated with a mathematical basis and the present study adopts this framework [8] By design, these autospectral and coherence models are in closed form and they have a simple analytical structure to facilitate interrogation and interpretation of voluminous data points on autospectra and coherences. A comparison of the measured autospectra of ambient atmospheric boundary layer turbulence dimensionless frequency f z/U, where z is the mast height and U is the mean wind speed These (ABL) and wake turbulence shows that the ABL autospectrum has gone through changes in energy autospectra were experimentally generated theshould samehelp location a wind farm over distribution with respect to frequency.
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