Optimal tuned mass damper for a spar buoy floating wind turbine to mitigate fatigue damage

Abstract

© 2016, International Society of Science and Applied Technologies. All rights reserved. Nowadays, there has been an increasing interest in wind energy in deep water. The increasing size of the turbine and the compliance of the floating support structure make the floating wind turbine vulnerable in the harsh environment. Due to the cyclic loads caused by platform pitching and tower bending motion, the fatigue damage at the tower base is relatively high. An optimal design of tuned mass damper (TMD) can reduce the structural load effectively. This paper deals with design optimization of a TMD for a spar buoy floating wind turbine to minimize the fatigue damage at the tower base. A high-fidelity nonlinear simulator is used to model the coupled wind turbine and TMD system. With consideration of uncertainties in environmental conditions and millions of Gaussian white noise random variables accounted for wind turbulences and irregular waves, the objective function becomes a high-dimensional probability integral and Subset Stochastic Optimization (SSO) method is used to solve this optimization problem. A novel acceptance-rejection sampling with subset simulation (ARS-SS) for reliability analysis is proposed for simulating samples required in SSO with less computational cost. In this study, ARS-SS sampling algorithm saves 75% computational cost when compared with the original ARS and the identified optimal TMD can reduce the fatigue damage by 15%.