Robust adaptive analysis of dynamic responses of wave energy converters

Author:

Wang YingguangORCID

Abstract

PurposeThe purpose of this paper is to exploit a new and robust method to forecast the long-term extreme dynamic responses for wave energy converters (WECs).Design/methodology/approachA new adaptive binned kernel density estimation (KDE) methodology is first proposed in this paper.FindingsBy examining the calculation results the authors has found that in the tail region the proposed new adaptive binned KDE distribution curve becomes very smooth and fits quite well with the histogram of the measured ocean wave dataset at the National Data Buoy Center (NDBC) station 46,059. Carefully studying the calculation results also reveals that the 50-year extreme power-take-off heaving force value forecasted based on the environmental contour derived using the new method is 3572600N, which is much larger than the value 2709100N forecasted via the Rosenblatt-inverse second-order reliability method (ISORM) contour method.Research limitations/implicationsThe proposed method overcomes the disadvantages of all the existing nonparametric and parametric methods for predicting the tail region probability density values of the sea state parameters.Originality/valueIt is concluded that the proposed new adaptive binned KDE method is robust and can forecast well the 50-year extreme dynamic responses for WECs.

Publisher

Emerald

Subject

Computational Theory and Mathematics,Computer Science Applications,General Engineering,Software

Reference20 articles.

1. Environmental contours based on inverse SORM;Marine Structures,2018

2. Environmental wave contours by inverse FORM and Monte Carlo Simulation with variance reduction techniques;Ocean Engineering,2021

3. Kernel density estimation (KDE) with adaptive bandwidth selection for environmental contours of extreme sea states,2016

4. The effect of environmental contour selection on expected wave energy converter response;Journal of Offshore Mechanics and Arctic Engineering,2019

5. Predicting wave heights for marine design by prioritizing extreme events in a global model;Renewable Energy,2020

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