Statistical model for fragility estimates of offshore wind turbines subjected to aero-hydro dynamic loads

Jharna Pokhrel and Junwon Seo

Renewable Energy, 2021, vol. 163, issue C, 1495-1507

Abstract: This paper aims to develop statistical regression-based models to estimate responses of monopile foundation 5 MW Offshore Wind Turbines (OWTs) subjected to multi-wind-and-wave loads and to assess its fragilities. Establishing the regression models began with the use of the Latin Hypercube Sampling (LHS) method incorporating 5 MW OWT input parameters related to structural and loading conditions along with material properties. With the LHS-based input parameters, 120 OWT computational models were created through Fatigue, Aerodynamic, Structures, and Turbulence (FAST) tools developed by the National Renewable Energy Laboratory (NREL). Critical responses, such as tower-top deflection, corresponding to each of the models were determined by performing its FAST aero-hydro dynamic simulations. The regression models involved a series of developed explanatory functions based on a matrix of the FAST responses and LHS parameters under a Stepwise Multiple Linear Regression (SMLR) approach. Multi-wind-and-wave fragilities were estimated for each of the critical responses of the 120 OWT models. Key findings showed that the wind-sensitive blade tip deflection resulted in the fragility of 99% at a critical wind speed of 75 m/s and a wave height of 20m, while the mudline flexural moment resulting from the same wind speed and wave height caused the fragility up to 98%.

Keywords: Offshore wind turbine; Fragility; Wind; Wave; Regression model; FAST (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:163:y:2021:i:c:p:1495-1507

DOI: 10.1016/j.renene.2020.10.015

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