In line with the EU’s stated aim of becoming the first carbon neutral continent by 2050, nations across Europe are ploughing significant resources into boosting output from a range of renewable energy sources. As a result, it is unsurprising that new research has found that the market for wind turbine materials alone is set to double over the next six years, across both structural and non-structural materials.
Operators have already had great success in lowering the levelised cost of wind farms through economies of scale. Now, with CAPEX costs set to reach $45bn by 2026 – nearly half of which will be spent on materials – the next step is embracing disruptive technologies which will enable the creation of much leaner designs.
Not only can we improve the efficiency of future turbines and reduce the cost of raw materials, but, given the fact that many of the structural materials used to create them are virtually impossible to recycle, it will also help make newer wind farms even more environmentally friendly.
In order to identify and address the inefficiencies in existing designs, engineers need access to vast amounts of data about structural integrity and operational conditions – in many cases, a lot more data than they actually possess. Crucially, this needs to be real-world data, not idealised states which are often hypothesised during the design phase. For example, if the current design of an offshore wind farm is liable to lead to turbine blades cracking or marine growths occurring on the asset, this needs to be present in the data so that practical refinements can be made.
Understanding these requirements, there are critical/important gains that can be made by adjusting the existing development process. Today, around 20,000 engineering hours are spent during the design phase of wind farm foundations. How about leveraging this investment in predictive power, in operations once the wind farm is delivered?
The solution is to deploy digital twins on existing assets, enabling the creation of a digital feedback loop from design to operations. This cutting edge approach not only provides engineers with relevant operational data to understand how existing assets are behaving under operating conditions, it also allows them to model how different design changes might impact the assets behaviour, enabling the next generation of design to be more resilient, more sustainable , and optimised for their environment.
The GODESS Project
As part of its push towards a carbon neutral future, the EU has invested heavily into digital twin technology, including awarding Akselos a research grant of €1.4m to maximise design efficiency and accelerate the energy transition. The grant, which is given to firms with a proven track record of R&D innovation and excellence, was awarded to Akselos because of our revolutionary reduced order modelling which is 1000 times faster than conventional analysis software.
According to the European Institute of Innovation and Technology the project – known as GODESS (Global Optimal DEsign of Support Structures) – could reduce the cost of materials for substructures by up to 25%. The findings from Frost & Sullivan indicate that realisation of such potential design benefits could be worth close to €5bn in savings for operators – savings which could then be passed down the line to consumers and help speed up the energy transition process. In addition, the data from digital twins will deliver much faster and much more accurate REX (Return on Experience), a further accelerator for the shift towards renewables.
Digital twins are going to be central to the design, deployment, and operation of energy assets moving forward. Contact us today to learn more about how using our software can increase accuracy and avoid over-designing, helping you to win more tender bids.