Comparative analysis of Gaussian Process power curve models based on different stationary covariance functions for the purpose of improving model accuracy

Ravi Kumar Pandit and David Infield

Renewable Energy, 2019, vol. 140, issue C, 190-202

Abstract: Gaussian Process (GP) models are increasingly finding application in wind turbine condition monitoring and in particular early fault detection. GP model accuracy is greatly influenced by the choice and type of the covariance functions (used to described the similarity between two given data points). Hence, the appropriate selection and composition of covariance functions is essential for accurate GP modelling.

Keywords: Condition monitoring; Power curve; Covariance functions; Gaussian process (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:140:y:2019:i:c:p:190-202

DOI: 10.1016/j.renene.2019.03.047

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