Projects per year
Abstract
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.
Original language | English |
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Pages (from-to) | 94-101 |
Number of pages | 8 |
Journal | IEEE Transactions on Sustainable Energy |
Volume | 3 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2012 |
Keywords
- wind power generation
- energy conversion
- power generation reliability
Fingerprint Dive into the research topics of 'Wind turbine condition assessment through power curve copula modeling'. Together they form a unique fingerprint.
Projects
- 2 Finished
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HiDEF. Supergen 3 HDPS Renewal Core and Pluses
Infield, D., Ault, G., Bell, K., Burt, G., Finney, S., Fletcher, J., Johnstone, C., Kelly, N., Kockar, I., McGregor, P. & Williams, B.
EPSRC (Engineering and Physical Sciences Research Council)
1/07/09 → 30/09/13
Project: Research
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Techniques for Electric Power Systems with High Penetrations of Renewable Non-Thermal Generation
Infield, D., Anaya-Lara, O., Ault, G., Bell, K., Fletcher, J., Kockar, I., Leithead, B., McArthur, S. & McDonald, J.
EPSRC (Engineering and Physical Sciences Research Council)
1/04/09 → 31/03/13
Project: Research
Research Output
- 138 Citations
- 1 Poster
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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
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