A new methodology is derived to transform between an ideal zero-turbulence power curve and practical power curves representing wind turbine performance in irregular winds. The derivation is based on substituting a theoretical distribution of the wind process in place of a single mean wind speed, truncating the wind-speed distribution at the rated power of the turbine, and then applying random process theory to derive analytical expressions based on the expected power and standard deviation of power of the parts of the distribution above and below the rated speed. The resulting expressions explicitly include the effects of turbulence intensity and can be used with higher statistical moments of the wind. The limited number of parameters needed to develop a practical power curve and to predict the standard deviation of the power can be estimated from limited time-domain simulations or from measured field data. The new methodology can also be used to generate a turbulence-free power curve from power data measured in turbulent winds. The accuracy of the new method is demonstrated by benchmarking expected power and standard deviation of power against predictions based on using direct numerical simulation and against an equivalent power curve resulting from direct field measurement.

中文翻译：

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利用风过程统计数据变换风力发电机功率曲线


导出了一种新的方法来在理想的零湍流功率曲线和代表不规则风中风力涡轮机性能的实际功率曲线之间进行转换。推导的基础是用风过程的理论分布代替单个平均风速，截断风轮机额定功率下的风速分布，然后应用随机过程理论根据期望推导解析表达式额定转速以上和以下各部分功率分布的功率及标准差。得到的表达式明确包括湍流强度的影响，并且可以与风的更高统计矩一起使用。开发实用功率曲线和预测功率标准偏差所需的有限数量的参数可以从有限的时域模拟或测量的现场数据来估计。新方法还可用于根据在湍流风中测量的功率数据生成无湍流功率曲线。通过将预期功率和功率标准偏差与基于使用直接数值模拟的预测以及直接现场测量产生的等效功率曲线进行基准比较，证明了新方法的准确性。