Risk‐Based Structural Seismic Response Assessment of Large‐Scale Jacket‐Supported Offshore Wind Turbines

ABSTRACT Offshore wind energy is growing as a major contributor to achieving the current targets of reaching net‐zero carbon emissions globally, offering a scalable, reliable, and cost‐competitive energy source. With the worldwide momentum of investing in wind energy infrastructure, offshore wind farms are now being constructed in seismically active regions, along with ambitious future expansion plans in countries of moderate‐to‐high seismic activity. To date, limited data exists on the long‐term performance of large‐scale offshore wind turbines under earthquake loading, which necessitates a comprehensive understanding of the performance of such assets under moderate and extreme seismic events. This study provides a risk‐based assessment of the seismic performance of jacket‐supported offshore turbines which have received less attention in the literature compared to monopile‐supported offshore turbines, and can provide a more attractive solution in seismic regions. The performance of a four‐legged, X‐braced reference jacket structure supporting a 10 MW turbine located in a reference site of high seismicity, where different source types drive the seismic hazard, is investigated using response history analysis. Particular emphasis is given to the hazard‐consistent ground‐motion selection methodology required for properly evaluating the response considering several seismic response measures. To achieve this, 300 nonlinear response history analyses are conducted to investigate the maximum acceleration and drift demands at the rotor‐nacelle assembly (RNA) level across a range of seismic hazard intensity levels. Additionally, conditional fragility curves for different acceleration and drift limits and demand curves showing the annual rate of exceedance as a function of demand values are reported. The study highlights the high sensitivity of the obtained results to the demand limit definition for both drifts and accelerations at the RNA level. This emphasizes the need for proper and consistent definitions of demand limits and acceptance criteria to provide reliable risk‐based damage and loss assessments.