Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoring

Ravi Pandit
, David Infield

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

11 Citations (Scopus)

62 Downloads (Pure)

11 Citations
9 Article
3 Conference contribution book
1 Proceeding

9 results

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2019
Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy
Pandit, R. K. & Infield, D., 30 Sept 2019, In: Renewable Energy. 140, p. 190-202 13 p.
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Comparison of advanced non-parametric models for wind turbine power curves
Pandit, R. K., Infield, D. & Kolios, A., 8 Jul 2019, In: IET Renewable Power Generation. 13, 9, p. 1503-1510 8 p.
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138 Downloads (Pure)
2018
Incorporating air density into a Gaussian process wind turbine power curve model for improving fitting accuracy
Pandit, R. K., Infield, D. & Carroll, J., 22 Oct 2018, In: Wind Energy. p. 1-14 14 p.
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Comparative assessments of binned and support vector regression-based blade pitch curve of a wind turbine for the purpose of condition monitoring
Pandit, R. K. & Infield, D., 12 Oct 2018, (E-pub ahead of print) In: International Journal of Energy and Environmental Engineering. p. 1-8 8 p.
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Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoring
Pandit, R. K. & Infield, D., 10 Oct 2018, In: Journal of Physics: Conference Series. 1102, 1, 10 p., 012037 .
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Comparison of binned and Gaussian Process based wind turbine power curves for condition monitoring purposes
Pandit, R. K. & Infield, D., 1 Sept 2018, In: Journal of Maintenance Engineering. 2, 12 p.
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Gaussian process operational curves for wind turbine condition monitoring
Pandit, R. & Infield, D., 22 Jun 2018, In: Energies. 11, 7, 20 p.
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Performance assessment of a wind turbine using SCADA based Gaussian Process model
Pandit, R. K. & Infield, D., 20 Jun 2018, In: International Journal of Prognostics and Health Management. 9, 1, 8 p., 023.
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SCADA-based wind turbine anomaly detection using Gaussian Process (GP) models for wind turbine condition monitoring purposes
Pandit, R. K. & Infield, D., 31 May 2018, (E-pub ahead of print) In: IET Renewable Power Generation. 9 p.
Research output: Contribution to journal › Article › peer-review

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Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoring

Research output

Search results

2019

2018