Browsing by Author "Rinker, Jennifer Marie"
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Item Open Access An Empirically Based Stochastic Turbulence Simulator with Temporal Coherence for Wind Energy Applications(2016) Rinker, Jennifer MarieIn this dissertation, we develop a novel methodology for characterizing and simulating nonstationary, full-field, stochastic turbulent wind fields.
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.
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.
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.
The four wind datasets were intentionally chosen from locations around the world so that they had significantly different ambient atmospheric conditions.
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.
EJDs have the added benefit of being able to generate samples of wind parameters that reflect the characteristics of a particular site.
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.
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.
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.
The effect of temporal coherence was calculated as a percent increase in the lifetime load over the base value with no temporal coherence.
Item Open Access Phase Coherence in Wind Data and Simulation(2014) Rinker, Jennifer MarieNovel wind turbine designs are deemed acceptable through a simulation-based certification process that involves generating a synthetic wind record and using it as an input to a computer model of the turbine. Naturally, whether the simulation loads reflect the loads that the turbine would actually experience depends on the accuracy of the wind turbine model and, more importantly, on the accuracy of the method used to generate the synthetic wind record. The simulation methods that are commonly used for this purpose are spectral-based and produce Gaussian, stationary random fields. These methods prescribe a power spectral density (PSD) of the wind velocity, which fixes the magnitudes of the Fourier components, then assumes that the Fourier phase angles are independent and uniformly distributed. An inverse Fast Fourier Transform (IFFT) is then used to transform the wind velocity field to the time domain.
This thesis applies the concept of phase coherence---i.e., Fourier phase angles that are not independent---to the stochastic modeling and simulation of wind velocity fields. Using a large dataset available from the National Wind Technology Center (NWTC), a joint distribution is characterized for the mean wind speed U, turbulence σu, Kaimal length scale L, and a metric for the degree of phase coherence in wind data, R. The correlations between these four parameters, the vertical height, and another phase coherence parameter are presented; only U, σu, and L have any significant degree of correlation. The joint distribution is used to generate synthetic wind records, which are then compared with measured data that have the same parameter values. For data with low to medium coherence values, the synthetic records have a similar qualitative appearance to the data. For high levels of phase coherence, the records simulated with the proposed model were qualitatively different from records with the same parameter values due to the variation of the phase difference spread in the spectral domain. Lastly, the importance of correctly modeling phase coherence is demonstrated by using the data and the synthetic records as inputs to a single-degree-of-freedom (SDOF) oscillator and comparing the peak response statistics and damage equivalent loads (DELs).