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In this paper, a model based on a Gaussian Process is constructed for assessing the performance of a turbine. Here, a reference power curve using SCADA datasets from a healthy turbine is developed using a Gaussian Process and then is compared with a power curve from an unhealthy turbine. Error due to yaw misalignment is a common issue with wind turbine which causes underperformance, hence it is used as case study to test and validate the algorithm effectiveness.
|Number of pages||8|
|Journal||International Journal of Prognostics and Health Management|
|Publication status||Published - 20 Jun 2018|
- condition monitoring
- Gaussian Process models
- wind turbine anomaly detection
- wind turbine
- SCADA data
- SCADA analysis
Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracyPandit, R. K. & Infield, D., 30 Sep 2019, In: Renewable Energy. 140, p. 190-202 13 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile10 Citations (Scopus)6 Downloads (Pure)
Comparative analysis of binning and Gaussian Process based blade pitch angle curve of a wind turbine for the purpose of condition monitoringPandit, R. K. & Infield, D., 10 Oct 2018, In: Journal of Physics: Conference Series. 1102, 1, 10 p., 012037 .
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile
Comparative analysis of binning and support vector regression for wind turbine rotor speed based power curve use in condition monitoringPandit, R. & Infield, D., 13 Dec 2018, 2018 53rd International Universities Power Engineering Conference (UPEC). Piscataway, NJ: IEEE, 6 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution bookOpen AccessFile