基于高斯过程的风力机功率曲线建模

Jin Zhou, Peng Guo, Xue-Ru Wang
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引用次数: 13

摘要

对于风电场来说,风速与输出的关系可以用风力机的功率曲线来描述,是风力机功率性能的重要体现。基于风力机功率曲线的数学模型,可以设计风力机的性能监测。采用高斯过程建立风力机功率曲线模型。在贝叶斯背景下,本文旨在通过使用最大似然优化方法来寻找最优超参数来训练高斯过程。数据验证了模型的正确性。最后,在风力机功率曲线数学模型的基础上,利用控制图技术对风力机的状态进行监控。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of wind turbine power curve based on Gaussian process
For wind farms, the relationship between wind speed and output can be described by power curve of wind turbines, and it is an important embodiment of power performance of wind turbines. Based on the mathematical model of the power curve of wind turbine, monitoring performance of the wind turbine can be designed. Power curve model of wind turbines can be established by using Gaussian process. Within the Bayesian context, the paper aims to train the Gaussian process by using the maximum likelihood optimized approach to find the optimal hyperparameters. The model was validated by the data. Finally, based on the wind turbine power curve mathematical model, the states of the wind turbine can be monitored by using the technology of control charts.
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