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Effects of wind power spectrum analysis over resource assessment

机译:风电谱分析对资源评估的影响

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Based on the Van der Hoven's seminal work, wind power industry has adopted the 10 min mean time as the proper sampling to estimate resource assessment. However, research within the literature questions the generalization of the 10 min as a standard measure of minima dispersion due to the particular geographic characteristics where the measurements took place. In this work is analyzed the power spectrum of a high-frequency wind speed time series and its influence over the resource assessment in the region of La Ventosa, Oaxaca, Mexico. Power spectrum analysis from a monthly, seasonal, and annual time series results show a defined synoptic-scale, diurnal, and semi-diurnal variations, which changes in amplitude throughout the year. To study the influence of power spectrum in wind resource assessment were estimated and compared the capacity factors of a typical 2 MW wind turbine against measured wind speed with 1, 5, 10, 60, and 360 min mean times, we found that a maximum difference of 1.4 %. Resource assessment was also estimated using reanalysis data and WRF results, finding similar to high-resolution estimations, highlighting bias-corrected WRF performance, offering reliable results to model power performance after a statistical correction. (c) 2020 Elsevier Ltd. All rights reserved.
机译:根据van der Hoory的开创性工作,风电业采用了10分钟的平均时间作为估算资源评估的适当抽样。然而,文献内的研究提出了10分钟的推广作为由于测量发生的特定地理特征导致的最小色散的标准度量。在这项工作中,分析了高频风速时间序列的功率谱及其对La Ventosa,墨西哥瓦哈卡地区资源评估的影响。来自每月,季节性和年度时间序列结果的功率谱分析显示了定义的舞台标度,昼夜和半昼夜变化,这在全年中变化了幅度。为研究功率谱在风力资源评估中的影响估计,并将典型的2 MW风力涡轮机与测量风速的容量因素与1,5,10,60和360分钟的平均时代,我们发现最大差异1.4%。资源评估还使用重新分析数据和WRF结果估算,发现类似于高分辨率估计,突出显示偏置校正的WRF性能,在统计校正后提供可靠的结果。 (c)2020 elestvier有限公司保留所有权利。

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