Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm
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DOI：
10.1016/j.ymssp.2021.108530
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发表时间：
2021-11
期刊：
影响因子：
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通讯作者：
L. Bull;P. Gardner;T. Rogers;N. Dervilis;E. Cross;E. Papatheou;A. E. Maguire;C. Campos;K. Worden
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文献类型：
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作者：
L. Bull;P. Gardner;T. Rogers;N. Dervilis;E. Cross;E. Papatheou;A. E. Maguire;C. Campos;K. Worden
功率曲线反映了特定风力涡轮机的风速和输出功率之间的关系。该函数的精确回归模型在监控、维护、设计和规划中非常有用。然而，在实践中，测量并不总是与理想曲线相对应：功率削减将显示为(额外的)功能组件。这种多值关系不能用传统的回归方法来建模，而且相关数据通常在预处理过程中被移除。目前的工作提出了一种替代方法，可以在缩减的电力数据中推断多值关系。使用基于总体的方法，将概率回归模型的重叠混合应用于从运行中的风电场内的涡轮机记录的信号。结果表明，该模型能够准确地表示整个人口中的实际电力数据。
Power curves capture the relationship between wind speed and output power for a specific wind turbine. Accurate regression models of this function prove useful in monitoring, maintenance, design, and planning. In practice, however, the measurements do not always correspond to the ideal curve: power curtailments will appear as (additional) functional components. Such multivalued relationships cannot be modelled by conventional regression, and the associated data are usually removed during pre-processing. The current work suggests an alternative method to infer multivalued relationships in curtailed power data. Using a population-based approach, an overlapping mixture of probabilistic regression models is applied to signals recorded from turbines within an operational wind farm. The model is shown to provide an accurate representation of practical power data across the population.