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首页> 外文期刊>Sustainable Energy, IEEE Transactions on >Wind Turbine Condition Assessment Through Power Curve Copula Modeling
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Wind Turbine Condition Assessment Through Power Curve Copula Modeling

机译：通过功率曲线Copula建模评估风机状态

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摘要

Power curves constructed from wind speed and active power output measurements provide an established method of analyzing wind turbine performance. In this paper, it is proposed that operational data from wind turbines are used to estimate bivariate probability distribution functions representing the power curve of existing turbines so that deviations from expected behavior can be detected. Owing to the complex form of dependency between active power and wind speed, which no classical parameterized distribution can approximate, the application of empirical copulas is proposed; the statistical theory of copulas allows the distribution form of marginal distributions of wind speed and power to be expressed separately from information about the dependency between them. Copula analysis is discussed in terms of its likely usefulness in wind turbine condition monitoring, particularly in early recognition of incipient faults such as blade degradation, yaw, and pitch errors.
机译：根据风速和有功功率输出测量结果构建的功率曲线提供了一种分析风力涡轮机性能的既定方法。在本文中，建议将来自风力涡轮机的运行数据用于估计代表现有涡轮机功率曲线的双变量概率分布函数，以便可以检测到与预期行为的偏差。由于有功功率和风速之间的依赖关系很复杂，没有经典的参数化分布可以近似，因此提出了经验对数的应用。 copulas的统计理论允许风速和功率的边际分布的分布形式与关于它们之间的依赖性的信息分开表达。讨论了Copula分析在风力发电机状态监测中的可能用途，特别是在早期识别早期故障（例如叶片退化，偏航和俯仰误差）方面。

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