Impact of climate change on the design of multi-megawatt spar floating wind turbines

Abstract

Increased frequency and intensity of extreme events can make offshore constructions unsafe due to the rapidly shifting wind-wave pattern. The consequences of climate change are disregarded by the current performance-based design of offshore wind turbines (OWT). The Statistical Downscaling Model (SDSM) and Artificial Neural Network (ANN) algorithm are used to present a simplified approach to enable the inclusion of future climatic projections in the design of spar-floating wind turbines. A two-variable statistical equation employing an Artificial Neural Network is established for calculating wind-induced wave height for the North Sea and West Coast of India, which is a valuable parameter for the site-specific design of offshore constructions. Under the SSP2-4.5 scenario, the North Sea's most likely wind speed is anticipated to decrease by 11 %, whereas the west coast of India experiences a slight decrease in wind speed. Serviceability responses, such as tower deflection, rotation, and nacelle acceleration, are expected to rise by 8–10 %. In contrast, a decrease in these responses is projected in the North Sea due to a decrease in future wind speed and wave height. Climate change has a greater impact on shutdown conditions than on normal operations, primarily due to the pronounced shifts in extreme climate conditions.