This case study was submitted jointly by the World Economic Forum (WEF) and technology company Akselos.
Technology approach(es) used to catalyse investment: Implementation of a data platform or digital twin for greater transparency over performance
Finance approach(es) used to catalyse investment: De-risking mechanisms or blended finance
In 2019, Irish electricity company ESB was seeking a solution to help them understand the structural health of a 47-year-old pumped storage station, to determine if the asset could continue to operate safely into the future. As Ireland’s only pumped storage station, Turlough Hill generates up to 292MW into the Irish grid during peak demand periods. Approaching 47 years of operation, ESB started to ask fundamental questions about structural integrity and operational risk. ESB’s structural engineers were also looking for innovative ways to monitor the asset's condition if it were to continue operating. Much of the hydro station is simply not accessible, as it is buried into a mountain, and even the internal structure is hard to inspect. The challenge was intensified due to the sparse analogue data that was available to digitise the asset and build out a complete 3D view of the structure.
The solution was to create a structural model - or digital twin - of the entire asset. The physics-based model is an entire physical replica in absolute detail and accuracy. The model is set up to be updated with loading conditions and inspection data on a regular basis, providing the ability to carry out structural assessments based on the near-real-time condition. With the digital twin now deployed, the next stage is to connect the digital twin and real-life asset via sensors, to create a digital guardian that will give a constant, real-time picture of Turlough Hill’s structural condition.
The top drivers for this project were:
The desired outcomes were:
Top barriers were:
Given the commitment from ESB to put all necessary resources toward the project, Akselos was able to have access to the right engineers and data to work through the initial challenges. A dedicated team of Akselos engineers worked through the original design documentation - mostly hand drawings, site plans and calculations - to render a fully navigable 3D digital replica of the actual asset. To address the complexity of the operating conditions, ESB engineers worked with Akselos to build out a method to assess different cycles of operation. This is still part of the ongoing challenge for the future operation of the asset, and the team is continuing to evaluate the impact of the new cycles of operation and get an understanding of potential impact.
Firstly, and most importantly, the project increased the overall confidence of the operations teams that it had built a full understanding of the level of safety and the boundaries for safe operation of this mature asset.
Secondly, the project extended the asset life. In the absence of the Akselos technology, ESB would have had to resort to conventional engineering techniques to assess impacts and risks. These methods require a number of detailed assessments followed by structural work programs that typically cost EUR10-100 million. In the worst case, ESB might have been faced with a complete refurbishment of the main water distribution system, which would be in the EUR100 million plus price range. These costs were avoided by using the structural digital twin. Inspection scopes will be reduced by 30-40% compared to sectorial, prescriptive inspection methodologies. This will result in saving EUR100,000-200,000 per inspection.
ESB has evidenced through an isolated project that millions can be saved per asset each year with a structural digital twin. When scaled to a portfolio of critical assets, the economic benefits are significant. A critical part of Ireland’s renewable energy infrastructure is now resilient for a number of decades, allowing for time to consider the best options as the world transitions to a low-carbon economy.
Funding and financing
The project materialised as part of Free Electrons, an accelerator program of which ESB is a founding member. The program is designed to support start-ups who are working to transform the energy market with next-generation ideas. ESB and nine other global utilities work with each of the start-ups to refine and test their products with the potential to reach 80 million customers in more than 40 countries. Free Electrons is a utility ecosystem that is helping this very traditional sector adapt in the face of the energy transition to low-carbon, renewable energy. Akselos won a place among 400+ companies to compete with a selected few to run pilots within the Free Electron program. Without it, Akselos' ability to work with a company like ESB would have been unlikely at this stage.
Scalability is one of the unique selling propositions (USPs) of Akselos’ software. The technology allows for simulations to take place in minutes rather than months. The Akselos solution was developed with scalability in mind and can be applied to protect unlimited assets at the speed required for the energy transition. In addition to technical scalability, as a cloud-based solution it is well placed to scale across companies and the wider energy ecosystem.
There were no major risks identified for the implementation of the pilot scheme. Implementation risks were minimal and by design, as the potential issues were de-bugged in the implementation stage. The Akselos team is also experienced in addressing the sorts of engineering challenges that the hydro plant represented. Mitigation strategies included a rigorous delivery process and cross-references to recognised engineering standards for validation of each stage of the digital twin delivery.
The technology aims for a high return on investment (ROI) and rapid delivery, typically covering its own cost within one business cycle. In terms of human capital and ecosystem, Akselos technology has been designed to empower engineers with a better understanding of the challenges they face, to improve the way they work. Structural digital twins won't replace the need for engineers to interpret the data and make critical decisions; they simply aid the decisionmaking process with accurate, real-time information.
Structural digital twins are disruptive in nature and allow for the integration of new technologies and processes such as edge computing, artificial intelligence and machine learning. The societal risks for these emerging technologies are latent, and the digital twin gives the players in the ecosystem the possibility of adopting new business models based on higher value-added services.
Safety and security risk
There are no major risks identified. The technology supports customers to lower their carbon footprint. It does this by:
A key benefit is avoiding stranded assets for hydrocarbon industries by extending the life of old assets, rather than building new ones as the world transitions to a low-carbon economy.