An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications

<p>In this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields. </p><p>In this new method, nonstationarity is characterized and modeled via temporal coherence, which is quantified in the discre...

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Main Author: Rinker, Jennifer Marie
Other Authors: Gavin, Henri P
Published: 2016
Subjects:
Online Access:http://hdl.handle.net/10161/12119
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spelling ndltd-DUKE-oai-dukespace.lib.duke.edu-10161-121192016-10-16T03:34:24ZAn Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy ApplicationsRinker, Jennifer MarieEngineeringMechanical engineeringAlternative energynonstationaryreliabilityresponse surfacesstochastic turbulencetemporal coherencewind energy<p>In this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields. </p><p>In this new method, nonstationarity is characterized and modeled via temporal coherence, which is quantified in the discrete frequency domain by probability distributions of the differences in phase between adjacent Fourier components.</p><p>The empirical distributions of the phase differences can also be extracted from measured data, and the resulting temporal coherence parameters can quantify the occurrence of nonstationarity in empirical wind data.</p><p>This dissertation (1) implements temporal coherence in a desktop turbulence simulator, (2) calibrates empirical temporal coherence models for four wind datasets, and (3) quantifies the increase in lifetime wind turbine loads caused by temporal coherence.</p><p>The four wind datasets were intentionally chosen from locations around the world so that they had significantly different ambient atmospheric conditions.</p><p>The prevalence of temporal coherence and its relationship to other standard wind parameters was modeled through empirical joint distributions (EJDs), which involved fitting marginal distributions and calculating correlations.</p><p>EJDs have the added benefit of being able to generate samples of wind parameters that reflect the characteristics of a particular site.</p><p>Lastly, to characterize the effect of temporal coherence on design loads, we created four models in the open-source wind turbine simulator FAST based on the \windpact turbines, fit response surfaces to them, and used the response surfaces to calculate lifetime turbine responses to wind fields simulated with and without temporal coherence.</p><p>The training data for the response surfaces was generated from exhaustive FAST simulations that were run on the high-performance computing (HPC) facilities at the National Renewable Energy Laboratory.</p><p>This process was repeated for wind field parameters drawn from the empirical distributions and for wind samples drawn using the recommended procedure in the wind turbine design standard \iec.</p><p>The effect of temporal coherence was calculated as a percent increase in the lifetime load over the base value with no temporal coherence.</p>DissertationGavin, Henri P2016Dissertationhttp://hdl.handle.net/10161/12119
collection NDLTD
sources NDLTD
topic Engineering
Mechanical engineering
Alternative energy
nonstationary
reliability
response surfaces
stochastic turbulence
temporal coherence
wind energy
spellingShingle Engineering
Mechanical engineering
Alternative energy
nonstationary
reliability
response surfaces
stochastic turbulence
temporal coherence
wind energy
Rinker, Jennifer Marie
An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
description <p>In this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields. </p><p>In this new method, nonstationarity is characterized and modeled via temporal coherence, which is quantified in the discrete frequency domain by probability distributions of the differences in phase between adjacent Fourier components.</p><p>The empirical distributions of the phase differences can also be extracted from measured data, and the resulting temporal coherence parameters can quantify the occurrence of nonstationarity in empirical wind data.</p><p>This dissertation (1) implements temporal coherence in a desktop turbulence simulator, (2) calibrates empirical temporal coherence models for four wind datasets, and (3) quantifies the increase in lifetime wind turbine loads caused by temporal coherence.</p><p>The four wind datasets were intentionally chosen from locations around the world so that they had significantly different ambient atmospheric conditions.</p><p>The prevalence of temporal coherence and its relationship to other standard wind parameters was modeled through empirical joint distributions (EJDs), which involved fitting marginal distributions and calculating correlations.</p><p>EJDs have the added benefit of being able to generate samples of wind parameters that reflect the characteristics of a particular site.</p><p>Lastly, to characterize the effect of temporal coherence on design loads, we created four models in the open-source wind turbine simulator FAST based on the \windpact turbines, fit response surfaces to them, and used the response surfaces to calculate lifetime turbine responses to wind fields simulated with and without temporal coherence.</p><p>The training data for the response surfaces was generated from exhaustive FAST simulations that were run on the high-performance computing (HPC) facilities at the National Renewable Energy Laboratory.</p><p>This process was repeated for wind field parameters drawn from the empirical distributions and for wind samples drawn using the recommended procedure in the wind turbine design standard \iec.</p><p>The effect of temporal coherence was calculated as a percent increase in the lifetime load over the base value with no temporal coherence.</p> === Dissertation
author2 Gavin, Henri P
author_facet Gavin, Henri P
Rinker, Jennifer Marie
author Rinker, Jennifer Marie
author_sort Rinker, Jennifer Marie
title An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
title_short An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
title_full An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
title_fullStr An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
title_full_unstemmed An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications
title_sort empirically based stochastic turbulence simulator with temporal coherence for wind energy applications
publishDate 2016
url http://hdl.handle.net/10161/12119
work_keys_str_mv AT rinkerjennifermarie anempiricallybasedstochasticturbulencesimulatorwithtemporalcoherenceforwindenergyapplications
AT rinkerjennifermarie empiricallybasedstochasticturbulencesimulatorwithtemporalcoherenceforwindenergyapplications
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