In the wind industry, it is important to assess a turbine systems response under different wind profiles. For instance, a wind-to-power relationship is crucial for wind power forecast, and a wind-to-stress relationship is important for selecting critical design parameters meeting the reliability requirement. Given the complexity involved in a turbine system, it is impossible to write a neat, analytical expression to underlie the above-mentioned relationships. Almost invariably does the wind industry resort to data driven methods for a solution, namely that wind data and the corresponding turbine response data (bending moments or power outputs) are used together to fit empirically the functional relationship of interest. This paper presents a couple of nonparametric data analytic methods relevant to wind energy applications with real life example for demonstration.
- International Gas Turbine Institute
Data Analytics Methods for Wind Energy Applications
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Ding, Y, Tang, J, & Huang, JZ. "Data Analytics Methods for Wind Energy Applications." Proceedings of the ASME Turbo Expo 2015: Turbine Technical Conference and Exposition. Volume 9: Oil and Gas Applications; Supercritical CO2 Power Cycles; Wind Energy. Montreal, Quebec, Canada. June 15–19, 2015. V009T46A020. ASME. https://doi.org/10.1115/GT2015-43286
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