...
首页> 外文期刊>Renewable energy >Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy
【24h】

Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy

机译:外推风速时间序列与魏布尔分布,以评估风轮机高度的风资源:以意大利南部沿海地区为例

获取原文
获取原文并翻译 | 示例
           

摘要

Increasing knowledge on wind shear models to strengthen their reliability appears as a crucial issue, markedly for energy investors to accurately predict the average wind speed at different turbine hub heights, and thus the expected wind energy output. This is particularly helpful during the feasibility study to abate the costs of a wind power project, thus avoiding installation of tall towers, or even more expensive devices such as LIDAR or SODAR. The power law (PL) was found to provide the finest representation of wind speed profiles and is hence the focus of the present study. Besides commonly used for vertical extrapolation of wind speed time series, the PL relationship between "instantaneous" wind profiles was demonstrated by Justus and Mikhail to be consistent with the height variation of Weibull distribution. Therefore, in this work a comparison is performed between these two different PL-based extrapolation approaches to assess wind resource to the turbine hub height: (ⅰ) extrapolation of wind speed time series, and (ⅱ) extrapolation of Weibull wind speed distribution. The models developed by Smedman-Hogstrom and Hogstroem (SH), and Panofsky and Dutton (PD) were used to approach (ⅰ), while those from Justus and Mikhail (JM) and Spera and Richards (SR) to approach (ⅱ). Models skill in estimating wind shear coefficient was also assessed and compared. PL extrapolation models have been tested over a flat and rough location in Apulia region (Southern Italy), where the role played by atmospheric stability and surface roughness, along with their variability with time and wind characteristics, has been also investigated. A 3-year (1998-2000) 1-h dataset, including wind measurements at 10 and 50 m, has been used. Based on 10-m wind speed observations, the computation of 50-m extrapolated wind resource, Weibull distribution and energy yield has been made. This work is aimed at proceeding the research issue addressed within a previous study, where PL extrapolation models were tested and compared in extrapolating wind resource and energy yield from 10 to 100 m over a complex-topography and smooth coastal site in Tuscany region (Central Italy). As a result, wind speed time series extrapolating models proved to be the most skilful, particularly PD, based on the similarity theory and thus addressing all stability conditions. However, comparable results are returned by the empirical JM Weibull distribution extrapolating model, which indeed proved to be preferable as being: (ⅰ) far easier to be used, as z_0-, stability-, and wind speed time series independent; (ⅱ) more conservative, as wind energy is underpredicted rather than overpredicted.
机译:增加对风切变模型的了解以增强其可靠性似乎是一个至关重要的问题,这对于能源投资者而言,显然是要准确地预测不同涡轮机轮毂高度处的平均风速,从而可以预测风能输出。这在进行可行性研究以减少风电项目的成本,从而避免安装高塔或什至更昂贵的设备(如LIDAR或SODAR)时特别有用。幂律(PL)被发现可以最好地表示风速曲线,因此是本研究的重点。 Justus和Mikhail证明,“瞬时”风廓线之间的PL关系除了常用于风速时间序列的垂直外推外,还与威布尔分布的高度变化一致。因此,在这项工作中,在这两种不同的基于PL的外推方法之间进行了比较,以评估风能对涡轮轮毂高度的影响:(ⅰ)风速时间序列的外推,以及(ⅱ)Weibull风速分布的外推。由Smedman-Hogstrom和Hogstroem(SH)以及Panofsky和Dutton(PD)开发的模型用于(ⅰ),而Justus和Mikhail(JM)以及Spera和Richards(SR)的模型用于(ⅱ)。还评估并比较了估算风切变系数的模型技巧。 PL外推模型已经在Apulia地区(意大利南部)的平坦和粗糙地区进行了测试,该地区还研究了大气稳定性和表面粗糙度以及它们随时间和风的变化而发挥的作用。使用了3年(1998-2000)1小时数据集,包括在10和50 m处的风速测量。根据10米的风速观测,计算了50米的外推风资源,威布尔分布和能量产量。这项工作旨在推进先前研究中解决的研究问题,在该研究中,测试并比较了PL外推模型,在复杂的地形和光滑的托斯卡纳地区(意大利中部)上推算出10至100 m的风能和能源产量)。结果,基于相似性理论,风速时间序列外推模型被证明是最熟练的,尤其是PD,因此可以解决所有稳定性条件。然而,经验JM Weibull分布外推模型返回了可比的结果,该模型确实被证明是更可取的:(ⅰ)更容易使用,因为z_0-,稳定性-和风速时间序列独立; (ⅱ)更保守,因为风能被低估而不是被高估。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号