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.
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ASME Turbo Expo 2015: Turbine Technical Conference and Exposition
June 15–19, 2015
Montreal, Quebec, Canada
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
978-0-7918-5680-2
PROCEEDINGS PAPER
Data Analytics Methods for Wind Energy Applications Available to Purchase
Yu Ding,
Yu Ding
Texas A&M University, College Station, TX
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Jiong Tang,
Jiong Tang
University of Connecticut, Storrs, CT
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Jianhua Z. Huang
Jianhua Z. Huang
Texas A&M University, College Station, TX
Search for other works by this author on:
Yu Ding
Texas A&M University, College Station, TX
Jiong Tang
University of Connecticut, Storrs, CT
Jianhua Z. Huang
Texas A&M University, College Station, TX
Paper No:
GT2015-43286, V009T46A020; 9 pages
Published Online:
August 12, 2015
Citation
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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