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Abstract
The conventional means of assessing the performance of a wind turbine is through consideration of its power curve which provides the relationship between power output and measured wind speed. In this paper it is shown how the joint probability distribution of power and wind speed can be learned from data, rather than from examination of the implied function of the two variables. Such an approach incorporates measures of uncertainty into performance estimates, allows inter-plant performance comparison, and could be used to simulate plant operation via sampling. A preliminary model is formulated and fitted to operational data as an illustration.
Original language | English |
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Pages (from-to) | 965-966 |
Number of pages | 2 |
Journal | IEEE Transactions on Power Systems |
Volume | 26 |
Issue number | 2 |
Early online date | 23 Sept 2010 |
DOIs | |
Publication status | Published - 1 May 2011 |
Keywords
- data models
- energy conversion
- joints
- monitoring
- time series analysis
- wind power generation
- wind speed
- wind turbines
- power generation reliability
Fingerprint
Dive into the research topics of 'A copula model of wind turbine performance'. Together they form a unique fingerprint.Projects
- 1 Finished
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Techniques for Electric Power Systems with High Penetrations of Renewable Non-Thermal Generation
Infield, D. (Principal Investigator), Anaya-Lara, O. (Co-investigator), Ault, G. (Co-investigator), Bell, K. (Co-investigator), Fletcher, J. (Co-investigator), Kockar, I. (Co-investigator), Leithead, B. (Co-investigator), McArthur, S. (Co-investigator) & McDonald, J. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/04/09 → 31/03/13
Project: Research
Research output
- 92 Citations
- 1 Poster
-
Wind turbine performance assessment & power curve outlier rejection using copula modelling
Zorzi, G., Stephen, B. & McMillan, D., 19 Jun 2018. 1 p.Research output: Contribution to conference › Poster
Open AccessFile