Abstract
Knowledge about the scaling of steel mass of monopiles is needed to decide for which service life an offshore wind farm should be planned. A computer-aided method to optimize monopiles for different fatigue lifetimes was developed. The optimization was performed with a genetic algorithm. Fatigue constraints were evaluated with aero-hydro-elastic load simulations in the time-domain. Importance sampling was applied to reduce the required number of load cases to 120 (only 7% of total amount of load cases). The optimization was tested for an 8 MW offshore wind turbine. Results prove that the developed method using importance sampling is suitable to gain fast and accurate optimization results. Only 5% more steel is needed to raise the fatigue lifetime from 25 to 35 years for a design without inspections. The increase of steel mass flattens out towards longer fatigue lifetimes since the structure becomes stiffer and less prone to wave excitation. This is valuable input to decide on the ideal service lifetime and maintenance strategies.
Highlights
Offshore wind energy has developed rapidly in the past two decades - from small near shore wind farms up to large turbines in deeper water today
The load cases left from the red line belong to design load cases (DLC) 1.2, while the load cases on the right belong to DLC 6.4
cumulative density function (CDF) of fatigue damages from all load cases are shown in Figure 2
Summary
Offshore wind energy has developed rapidly in the past two decades - from small near shore wind farms up to large turbines in deeper water today. The design lifetime should be chosen considering various technical and economic aspects, such as scaling of structural dimensions, maintenance concepts, and financing. It should ideally be set in an early project phase already since it has large influence on other project decisions. This creates the need for fast methods to evaluate how the primary steel mass of monopiles scales for different fatigue lifetimes
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