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Reconstruction of atmospheric flows based on proper orthogonal decomposition method
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Date
2017
Author
Sevine, Tansu
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The placement of wind turbines in a wind farm, which is called micro-siting, is a crucial task in regard to the maximization of the energy production in a wind farm. The maximum energy production is only possible if all the wind turbines are placed in optimum locations. Although the micro-siting of wind turbines has many aspects to be considered such as wind field analysis, wake effect of the other turbines and accessibility, the wind speed is the most significant parameter. The statistical wind speed distribution over a wind farm is currently reconstructed from a wind field analysis, which is mostly based on statistical analysis of wind field data collected from a meteorological mast and numerical simulations of wind fields over the wind farm. The reconstruction of wind fields is mostly based on an interpolation process. In this study, a novel method based on the Proper Orthogonal Decomposition (POD) of fictitious wind fields is developed for the reconstruction of actual wind fields based on observation data. The fictitious wind fields for different wind sectors (wind direction) are obtained using an open-source Navier-Stokes solver, SU2, on high resolution terrain fitted computational grids. The POD based reconstruction of flow fields is first validated in 2D flow fields. It is then implemented for the reconstruction of wind fields over a wind farm. It is shown that the methodology developed is capable of reconstructing wind fields over wind farms and can effectively be employed for micro-siting of wind turbines.
Subject Keywords
Wind turbines.
,
Navier-Stokes equations.
,
Orthogonal decompositions.
,
Computational fluid dynamics.
,
Wind turbines
URI
http://etd.lib.metu.edu.tr/upload/12620743/index.pdf
https://hdl.handle.net/11511/26254
Collections
Graduate School of Natural and Applied Sciences, Thesis
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T. Sevine, “Reconstruction of atmospheric flows based on proper orthogonal decomposition method,” M.S. - Master of Science, Middle East Technical University, 2017.