Geospatial analysis of post-protection scour development in offshore wind farm

Abstract

Scour is one of the most serious challenges affecting the normal operation of offshore wind power. Whether measures for scour protection are effective directly affects the safety and economical efficiency of offshore wind farms. Data mining techniques and analytical tools based on monitoring data analysis play a critical role in making appropriate strategic decisions. Post-protection scour inspection was regularly monitored on a typical offshore wind farm containing 72 turbines installed with monopile foundations thrice over the course of two years. Geospatial properties of scour, including maximum scour depth (MSD), maximum scour extension and scouring and siltation volume, were analysed in detail. The possible autocorrelation of scour data measured for each turbine was identified using a data-driven decision making process. The characteristics of the investigated scour and their spatial dependence on the turbines of the inspected offshore wind farm generally showed an upward trend over time. A high–high area in the local geospatial dependency map of MSD was identified, and an equation was derived for predicting development of MSD. These findings show indications to reduce the operation and maintenance costs of offshore wind farms and improve the efficiency for upgrading scour protection on specific offshore wind foundations.