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Interaction Between the Atmospheric ...

St. Martin, Clara Mae.

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Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale./
作者:	St. Martin, Clara Mae.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
面頁冊數:	179 p.
附註:	Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
Contained By:	Dissertation Abstracts International78-10B(E).
標題:	Atmospheric sciences. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10263737
ISBN:	9781369784640

Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale.
St. Martin, Clara Mae.

Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 179 p.

Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.

Thesis (Ph.D.)--University of Colorado at Boulder, 2017.

Wind turbines and groups of wind turbines, or "wind plants", interact with the complex and heterogeneous boundary layer of the atmosphere. We define the boundary layer as the portion of the atmosphere directly influenced by the surface, and this layer exhibits variability on a range of temporal and spatial scales. While early developments in wind energy could ignore some of this variability, recent work demonstrates that improved understanding of atmosphere-turbine interactions leads to the discovery of new ways to approach turbine technology development as well as processes such as performance validation and turbine operations. This interaction with the atmosphere occurs at several spatial and temporal scales from continental-scale to turbine-scale. Understanding atmospheric variability over continental-scales and across plants can facilitate reliance on wind energy as a baseload energy source on the electrical grid. On turbine scales, understanding the atmosphere's contribution to the variability in power production can improve the accuracy of power production estimates as we continue to implement more wind energy onto the grid. Wind speed and directional variability within a plant will affect wind turbine wakes within the plants and among neighboring plants, and a deeper knowledge of these variations can help mitigate effects of wakes and possibly even allow the manipulation of these wakes for increased production. Herein, I present the extent of my PhD work, in which I studied outstanding questions at these scales at the intersections of wind energy and atmospheric science.

ISBN: 9781369784640Subjects--Topical Terms:

3168354
Atmospheric sciences.

Interaction Between the Atmospheric Boundary Layer and Wind Energy: From Continental-Scale to Turbine-Scale.
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500 $a Source: Dissertation Abstracts International, Volume: 78-10(E), Section: B.
500 $a Adviser: Julie K. Lundquist.
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520 $a Wind turbines and groups of wind turbines, or "wind plants", interact with the complex and heterogeneous boundary layer of the atmosphere. We define the boundary layer as the portion of the atmosphere directly influenced by the surface, and this layer exhibits variability on a range of temporal and spatial scales. While early developments in wind energy could ignore some of this variability, recent work demonstrates that improved understanding of atmosphere-turbine interactions leads to the discovery of new ways to approach turbine technology development as well as processes such as performance validation and turbine operations. This interaction with the atmosphere occurs at several spatial and temporal scales from continental-scale to turbine-scale. Understanding atmospheric variability over continental-scales and across plants can facilitate reliance on wind energy as a baseload energy source on the electrical grid. On turbine scales, understanding the atmosphere's contribution to the variability in power production can improve the accuracy of power production estimates as we continue to implement more wind energy onto the grid. Wind speed and directional variability within a plant will affect wind turbine wakes within the plants and among neighboring plants, and a deeper knowledge of these variations can help mitigate effects of wakes and possibly even allow the manipulation of these wakes for increased production. Herein, I present the extent of my PhD work, in which I studied outstanding questions at these scales at the intersections of wind energy and atmospheric science.
520 $a My work consists of four distinct projects. At the coarsest scales, I analyze the separation between wind plant sites needed for statistical independence in order to reduce variability for grid-integration of wind. At lower wind speeds, periods of unstable and more turbulent conditions produce more power than periods of stable and less turbulent conditions, while at wind speeds closer to rated wind speed, periods of unstable and more turbulent conditions produce less power than periods of stable and less turbulent conditions. Using these new, stability- and turbulence-specific power curves to calculate annual energy production (AEP) estimates results in smaller AEPs than if calculated using no stability and turbulence filters, which could have implications for manufacturers and operators. In my third project, I address the problem of expensive power production validation. Rather than erecting towers to provide upwind wind measurements, I explore the utility of using nacelle-mounted anemometers for power curve verification studies. I calculate empirical nacelle transfer functions (NTFs) with upwind tower and turbine measurements. The fifth-order and second-order NTFs show a linear relationship between upwind wind speed and nacelle wind speed at wind speeds less than about 9 m s--1 , but this relationship becomes non-linear at wind speeds higher than about 9 m s--1. The use of NTFs results in AEPs within 1 % of an AEP using upwind wind speeds. Additionally, during periods of unstable conditions as well as during more turbulent conditions, the nacelle-mounted anemometer underestimates the upwind wind speed more than during periods of stable conditions and less turbulence conditions at some wind speed bins below rated speed. Finally, in my fourth project, I consider spatial scales on the order of a wind plant. Using power production data from over 300 turbines from four neighboring wind farms in the western US along with simulations using the Weather Research and Forecasting model's Wind Farm Parameterization (WRF-WFP), I investigate the advantage of using the WFP to simulate wakes. During this case, winds from the west and north-northwest range from about 5 to 11 m s--1. A down-ramp occurs in this case study, which WRF predicts too early. The early prediction of the down-ramp likely affects the error in WRF-predicted power, the results of which show exaggerated wake effects.
520 $a While these projects span a range of spatio-temporal scales, a unifying theme is the important aspect of atmospheric variation on wind power production, wind power production estimates, and means for facilitating the integration of wind-generated electricity into power grids. Future work, such as universal NTFs for sites with similar characteristics, NTFs for waked turbines, or the deployment of lidars on turbine nacelles for operation purposes, should continue to study the mutually-important interconnections between these two fields. (Abstract shortened by ProQuest.).
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