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Articles

A novel transformation kernel density estimation method for predicting design force values of wave energy converters

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Pages 233-242 | Received 17 Jul 2022, Accepted 09 Dec 2022, Published online: 21 Dec 2022
 

ABSTRACT

This paper proposes to utilise an innovative transformation KDE (Kernel Density Estimation) method in order to more accurately calculate the sea state parameter distribution tails and to extrapolate well. This transformation KDE method is applied in predicting the probability distribution tails of a measured ocean wave dataset at National Data Buoy Center Station 51101, and its accuracy has been verified through comparisons with the prediction results via the parametric method. Next, the transformation KDE method is utilised for deriving an accurate 50-year environmental contour line based on the aforementioned measured wave dataset. The derived environmental contour line and some other contour lines obtained using parametric contour approaches are then applied for predicting the 50-year design PTO (Power-Take-Off) force values for a point absorber Wave Energy Converter (WEC). It is concluded that the predicted 50-year design PTO force value based on the proposed transformation KDE contour is more accurate.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work is supported by the National Natural Science Foundation of China [grant number 51979165].

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