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A new method to estimate the uncertainty of AEP of offshore wind power plants applied to Horns Rev 1

机译:一种估算海上风电站射门不确定性的新方法1

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The present article proposes a framework for validation of stationary wake models that wind developers can use to predict the energy production of a wind power plant more accurately. The application of this framework provides a new way to quantify the uncertainty of annual energy production predictions. Additionally this methodology enables the fair comparison of different wake models. Furthermore the methodology enables the estimation of how much information can be obtain from a measurement dataset to quantify model inadequacy. In the present work the proposed framework is applied to the Horns Rev 1 offshore wind power plant. The model uncertainty of a modified N. O. Jensen wake model under uncertain undisturbed flow conditions was studied. Evidence of model inadequacy is found in terms of a bias in the predicted AEP distribution. It was found that the use of the official power curve compensates the errors in the wake model, as a consequence a larger uncertainty of the overall model is predicted. Furthermore a study of wake model benchmarking based on filtered flow cases indicates that measurement uncertainty in the wind speed and wind direction is large enough to obtain any evidence of model inaccuracy even for the simplest wake models.
机译:本条提出了一个伪装风力开发人员可以使用的静止唤醒模型验证框架,以更准确地预测风力发电厂的能源生产。本框架的应用为量化年度能源生产预测的不确定性提供了一种新的方式。此外,这种方法可以实现不同的唤醒模型的公平比较。此外,该方法使得能够估计从测量数据集可以获得多少信息以量化模型不足。在本工作中,建议的框架应用于喇叭Rev 1海上风力发电厂。研究了不确定不受干扰流动条件下改进的N. O. O. O. O. O. O.的模型不确定性。在预测的AEP分布中的偏差方面,发现了模型不足的证据。结果发现,使用官方功率曲线补偿了唤醒模型中的错误,因此预测了整体模型的更大不确定性。此外,基于过滤的流箱的唤醒模型基准测试表明风速和风向的测量不确定性也足够大,以便为最简单的唤醒模型获得模型不准确的任何证据。

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