The concept of a twin of a physical system is decades old. But it’s only recently that computing power has grown sufficiently to enable the digital replication of highly complex and dynamic systems. In this overview, we look at how this innovative and crucial technology for the energy sector is rapidly becoming an essential tool for the design, maintenance and development of energy assets.

“Houston, we have a problem”

Anyone who has seen the 1995 docudrama Apollo 13 will have witnessed one of the first real-world applications of the concept of a digital replication of a physical system. The 1970 flight was planned as NASA’s third manned landing on the moon. But a major fault in the oxygen system meant that the three crew depended on improvised systems and procedures that were first tested on a twin of their spacecraft at Mission Control in Houston, TX. While more a hybrid analog/digital model than a full digital twin, the successful recovery of the astronauts demonstrated how changes to complex systems – with minimal margins for error – could be tested and proven remotely before being applied to the main system.

Models, shadows and twins

University of Michigan Professor Michael Grieves first proposed the concept to industrial-scale processes and systems in 2002. Originally referred to as a ‘doubleganger’ process – a pun on doppelganger – the phrase ‘digital twin’ was first coined by NASA’s Principal Technologist John Vickers in 2010. As defined by the Institute of Electrical and Electronics Engineers (IEEE), a digital twin does more than create a static digital model of a system or process; it dynamically receives and communicates data with the physical system in a two-way flow. (A one-way flow of information from the system to the digital representation is defined as a “digital shadow”).[1]

Uses and benefits

Digital twins can provide a range of benefits using technology based on Industrial Internet of Things (IIoT) protocols. Shell, for example, uses digital twin technology combined with AI to minimize the number of maintenance staff needed on-site – including on offshore platforms – as well as carry out predictive maintenance that can reduce costs.[2]

In the renewables sector, digital twins are set to become increasingly important as the grid becomes more distributed and more complex to manage efficiently. As PSC’s Adam Maloyd recognized in a 2022 blog post, “digital twinning could offer a robust way of testing the impact of technological innovations on a grid,” thereby avoiding significant risks as new technologies are introduced.

Meeting complex challenges

One example of an ambitious digital twin project along the lines mentioned in Adam’s blog post is the ENSIGN Energy System Digital Twin. This is currently under development in a research and development program led by the University of Strathclyde and SP Energy Networks, in partnership with many other companies and bodies.[3] ENSIGN will use data from the UK grid to help in the design of a multi-vector energy network twin. This includes wind, solar, tidal and non-electrical energy sources as part an integrated, reliable, resilient and affordable system. Findings from the 4-year research project will be made available to distribution network operators and their wider supply chain both in the UK and internationally. Other uses of digital twins include the ability to actively manage low-voltage distribution grids, as evidenced by the recent launch of the Siemens LV Insights X system.[4]

In theory, the ability to create a digital twin for any system – apart from the costs involved – is limited only by the computing power available and the technical capabilities of the team creating the twin. Other factors include the reliability and timeliness of the data feeds to and from the physical asset.

Success factors

The success of any digital twin relies on the quality of data it receives and feeds back into its physical counterpart. Not only does the data need to be standardized, it needs to be handled securely. As well as being commercially sensitive, the data could be a valuable target for hackers or hostile states. This means that the IT infrastructure that supports a digital twin needs to be robust, with exceptionally reliable connectivity and levels of cybersecurity across the whole network.[5]

Another success factor is the age-old measure of whether or not the expected results are worth the investment. It should provide measurable benefits that outweigh costs. So, the first task in the process of designing a digital twin is to set clear objectives and perform a basic cost/benefit analysis. The technology might be ‘rocket science,’ but the business case can be firmly brought down to earth.

How PSC can help

PSC has already developed a number of cutting-edge planning and analysis tools as a part of various innovation projects. PSC’s global energy experts can develop bespoke strategies to help plan and deploy digital twins. Contact us to find out more about our services to help power a more sustainable world.

References

[1] IEEE Access, Fuller, Fan, Day and Barlow, ‘Digital Twin: Enabling Technologies, Challenges and Open Research’, June 2020.  https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9103025

[2] Computer Weekly, Cliff Saran, ‘How Shell is fleshing out a digital-twin strategy’, October 2020. https://www.computerweekly.com/news/252491300/How-Shell-is-fleshing-out-a-digital-twin-strategy

[3] Build in Digital, Liam Turner, ‘Scottish digital twin project wins funding to inform future of UK energy’, May 2023. https://buildindigital.com/scottish-digital-twin-project-wins-funding-to-inform-future-of-uk-energy/

[4] Siemens, ‘Digital twin at core of new Siemens LV grid management software’, June 2023 https://industrialnews.co.uk/digital-twin-at-core-of-new-siemens-lv-grid-management-software/

[5] Decision Analytics Journal, Mohsen Attaran and Bilge Gokhan Celik, ‘Digital Twin: Benefits, use cases, challenges and opportunities’, March 2023. https://www.sciencedirect.com/science/article/pii/S277266222300005X#sec5