Selection and Design of Offshore Wind Turbine Foundations for the Red Sea Area - Egypt

The remarkable growth of offshore wind farms (OWF) coupled with the wide potential of new sites for deploying such farms, will require cost optimised solutions. Foundations and reliable method for select them to match site conditions forms part of such cost optimisation. By the end of 2015, Monopile systems represent more than 80% of the total installed foundations, while the other types such as Gravity Base, Tripods and Jackets represent the rest. Water depth and installation cost are the main criteria to select offshore foundation type. For this work we have selected three different locations in the Red Sea around the southern tip of Saini Peninsula, using Boolean Mask technique. The sites were located less than 20 km from the nearest port in Egypt, and have ample wind resource of speed above 9 m/s, and an average water depth is 25m. This work aims to provide foundation solutions appropriate to these sites. A Monopile system was designed for the 3 different sites taking into account their conditions – solid type, depth etc. The designs were achieved through a review of current state of art and additional analysis of the different technologies available for Monopile foundations. The results indicate that for the sandy soil type of the three chosen locations, Monopile foundation system (8 cm wall thickness, 6 m diameter with driven depths ranged from 16 to 24 m) are safe and economical to use for a modelled 5MW offshore wind turbine. All the structural analysis for the foundations in three sites was accomplished using ABAQUS software programme. A cost benefit analysis was conducted to update the outdated Monopile cost estimation providing relevance to sites selected. The results indicate that the achieved Monopile foundation designs are capable of supporting a 5 MW wind turbine for water depths in the range 20 m to 24 m pile depth Our economic analysis indicate that such foundations will have a of £4.9 million which compares well with published data.