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Impact of Spatio-Climatic Variability on Environment-Hosted Land-Based Renewables: Microclimates

Impact of Spatio-Climatic Variability on Environment-Hosted Land-Based Renewables: Microclimates
时空气候变化对环境承载的陆基可再生能源的影响:微气候
批准号:
NE/H010343/1
负责人:
Simon Watson
金额:
$20.63万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2010
资助国家:
英国
项目状态:
已结题
起止时间:
2010 至 --

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中文摘要
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英文摘要
Many current or projected future land-based renewable energy schemes are highly dependent on very localised climatic conditions, especially in regions of complex terrain. For example, mean wind speed, which is the determining factor in assessing the viability of wind farms, varies considerably over distances no greater than the size of a typical farm. Variations in the productivity of bio-energy crops also occur on similar spatial scales. This localised climatic variation will lead to significant differences in response of the landscape in hosting land-based renewables (LBR) and without better understanding could compromise our ability to deploy LBR to maximise environmental and energy gains. Currently climate prediction models operate at much coarser scales than are required for renewable energy applications. The required downscaling of climate data is achieved using a variety of empirical techniques, the reliability of which decreases as the complexity of the terrain increases. In this project, we will use newly emerging techniques of very high resolution nested numerical modelling, taken from the field of numerical weather prediction, to develop a micro-climate model, which will be able to make climate predictions locally down to scales of less than one kilometre. We will conduct validation experiments for the new model at wind farm and bio-energy crop sites. The model will be applied to the problems of (i) predicting the effect of a wind farm on soil carbon sequestration on an upland site, thus addressing the question of carbon payback time for wind farm schemes and (ii) for predicting local yield variations of bio-energy crops. Extremely high resolution numerical modelling of the effect of wind turbines on each other and on the air-land exchanges will be undertaken using a computational fluid dynamics model (CFD). The project will provide a new tool for climate impact prediction at the local scale and will provide new insight into the detailed physical, bio-physical and geochemical processes affecting the resilience and adaptation of sensitive (often upland) environments when hosting LBR.
期刊论文(3)
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会议论文
CFD Study of the Performance of an Operational Wind Farm and its Impact on the Local Climate
运行风电场性能及其对当地气候影响的 CFD 研究
DOI: --
发表时间: 2013
期刊: Proceedings
影响因子: --
作者: [Wylie SJ]
通讯作者: Wylie SJ
A Computational Fluid Dynamics (CFD) Study of Wind Flow Around a Model Forest: Comparison of Turbulent Closure Schemes and Varying Leaf Area Density
模型森林周围风流的计算流体动力学 (CFD) 研究:湍流闭合方案和变化叶面积密度的比较
DOI: --
发表时间: 2011
期刊: Scientific Proceedings
影响因子: --
作者: [Wylie SJ]
通讯作者: Wylie SJ
Validation of Microclimatic Wind Speed Data using a Computational Fluid Dynamics (CFD) Model
使用计算流体动力学 (CFD) 模型验证微气候风速数据
DOI: --
发表时间: 2012
期刊: Proceedings
影响因子: --
作者: [Wylie SJ]
通讯作者: Wylie SJ
Robotics and Artificial Intelligence for Critical Asset Monitoring (RAICAM)
  • 批准号:
    EP/X025004/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $33.8万
  • 财政年份:
    2023
  • 负责人:
    Simon Watson
  • 依托单位:
DD-DSM: Demonstration of Distributed Demand-side Management as a service to the UK grid operator
  • 批准号:
    TS/G002282/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $8.68万
  • 财政年份:
    2009
  • 负责人:
    Simon Watson
  • 依托单位:
海外基金