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Optimizing Stochastic Renewable Energy Systems

Optimizing Stochastic Renewable Energy Systems
优化随机可再生能源系统
批准号:
355687-2013
负责人:
Crawford, Curran
金额:
$2.33万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
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英文摘要
A key obstacle to the widespread adoption of renewable energy, such as wind and tidal power, is that by their nature they fluctuate over time. Traditionally, our power systems have been designed for conventional power sources such as hydro, coal and gas which can be commanded to run at-will to supply the fluctuations in the load being served by the system. In order to change that paradigm and make it possible to integrate more renewables onto the grid, the machines themselves must be designed with these fluctuations in mind, both in terms of maximizing their individual performance in turbulent winds and currents, and also by considering the larger systemic effects of the fluctuations during design. This research program aims to develop advanced analysis and optimization tools capable of tackling this problem. The first element of the research method will be the development and validation of advanced analysis tools capable of properly simulating through time advanced machine concepts which have non-standard blades with sweep and curvature, as well as fibre-reinforced structures that can induce beneficial flexing to offset unsteady aerodynamic loads. The next stage in the research will be to adapt the analysis tools so that they are less expensive to run, by obviating the need for pure time-based analysis with the application of new stochastic and probabilistic analysis approaches. The final stage of the program will glue together these computational tools, together with ones for control, cost, and the downstream electrical system, in a rigorously defined framework so that full system optimization studies can be carried out. The net output will be a capability to design wind and tidal turbines that are more cost effective than what is possible today. Canadian machine manufactures who already have a defined presence in the small to medium scale wind and tidal market will gain a competitive advantage globally. Designers working on the next generation of very large wind turbines will be enabled to create new concepts for larger rotors at a competitive cost for low-wind sites, to aid the widespread deployment of wind energy. Emerging tidal turbine designs will also be better able to withstand the harsh marine environment.
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Uncertainty quantification methods applied to wind energy systems
  • 批准号:
    RGPIN-2020-04511
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2022
  • 负责人:
    Crawford, Curran
  • 依托单位:
Uncertainty quantification methods applied to wind energy systems
  • 批准号:
    RGPIN-2020-04511
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2021
  • 负责人:
    Crawford, Curran
  • 依托单位:
Uncertainty quantification methods applied to wind energy systems
  • 批准号:
    RGPIN-2020-04511
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2020
  • 负责人:
    Crawford, Curran
  • 依托单位:
Optimizing Stochastic Renewable Energy Systems
  • 批准号:
    355687-2013
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.33万
  • 财政年份:
    2019
  • 负责人:
    Crawford, Curran
  • 依托单位:
国内基金
海外基金
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于梯度增强Stochastic Co-Kriging的CFD非嵌入式不确定性量化方法研究