Wind Turbine Condition Assessment Through Power Curve Copula Modeling
Wind Turbine Condition Assessment Through Power Curve Copula Modeling
复制标题
DOI：
10.1109/tste.2011.2167164
复制
发表时间：
2012-01-01
影响因子：
8.8
通讯作者：
Galloway, Stuart
中科院分区：
文献类型：
--
作者：
Gill, Simon;Stephen, Bruce;Galloway, Stuart
由风速和有功输出测量构建的功率曲线为分析风力机性能提供了一种成熟的方法。本文提出利用风力发电机组的运行数据来估计代表现有风力发电机组功率曲线的二元概率分布函数，从而检测出与预期行为的偏差。针对有功功率与风速之间的关系形式复杂，经典参数化分布无法近似描述的特点，提出了经验公式的应用；联线的统计理论允许风速和功率的边际分布形式与它们之间的依赖关系的信息分开表示。本文讨论了Copula分析在风力机状态监测中的应用，特别是在早期识别早期故障（如叶片退化、偏航和俯仰误差）方面。
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.