The offshore wind turbine installation market has matured significantly over the last decade. For the inexperienced observer, or even for some of the seasoned offshore professionals, the applied installation methods in Europe are all more, or less the same. However, only few of the existing installation vessels will be suitably equipped to meet the demands of the next generation turbines. To avoid an installation bottleneck, designers and equipment suppliers will remain focussed on purposeful innovation.
Wind turbine manufacturers will be eager to explain the big differences between their own and competitors’ turbines. The installation contractors bring their own expertise to the job and will confirm that every single installation site, and even every single turbine location can be vastly different. Also the designers of the installation jack-ups with dedicated cranes are always keen to point out the different capabilities between the units.
Nonetheless, from a global perspective, insights gained over the last decade have led to convergence in applied methods and technology. As long as none of the input parameters such as turbine sizes, environment, logistical infrastructure radically changes, it will be extremely difficult for innovative concepts to enter the market. Why is this the case?
• Developers have mastered the process of efficient field development, understand the risks and hence have honed their skills of efficient project execution.
• Wind turbine manufacturers know the current installation equipment, understand their potential and limitations and have found a good balance between modifying their scope (turbine) and requiring modifications to the installation jack-ups with their specialized cranes.
• Designers with proven products have met their promises in terms of timely delivery and delivery to specifications. This avoids both the time risk and technical risk.
• Yards like to price equipment that they know, since they can manage the risk. No need to include extra risk premium, and they can reliably predict their time to delivery.
