Kevin Jones, consultancy solutions manager at Schneider Electric UK&I says that efficient, low-carbon infrastructure cannot exist without more intelligent design. This is precisely why the proliferation of digital twins is gaining momentum across various industries.

A virtual representation of a physical object or process, digital twins enable a range of real-time insights that can enhance quality, performance, productivity, and energy efficiency. A digital twin is not an end result, product, outcome, or technology in and of itself. It’s a dynamic, data-supported framework that functions as a business enabler, solving real-world problems with real-world data.

One such challenge is that of sustainability. To drive towards sustainability goals, industry will become increasingly reliant on electrical infrastructure as the greenest energy source, and government and businesses are waking up to the idea of building performance in an all-electric world. While digital twins are becoming commonplace in industries such as construction and automotive, its potential is yet to be realised in electrical engineering and energy management.

A twin view of sustainability in electrical design

According to the IEA (International Energy Agency), by 2040, electricity use will double, reaching at least 40% of final energy consumption, and solar and wind will generate six times more electricity. However, today’s electrical distribution systems suffer from high levels of inefficiency. The answer is in more innovative design, aided by digital technologies such as digital twins, which provide a safe way to simulate changes and test, develop and evolve systems without high capital outlay. When ambitious Net Zero targets must be met, digital twins offer innumerable energy-saving opportunities.

For example, the Rock of Gibraltar has historically relied heavily on electrical generators but identified their use as a barrier to achieving net zero. Using a digital twin, they could design a battery storage solution and run simulations to improve efficiency. The next stage is AI-enabled automation – adaptive control strategies to suit electricity demands on the network, setting daily sustainability targets, such as a daily carbon production limit.

Similarly, a recent project for a major chemical company used a digital twin to simulate the effect on-site solar photovoltaics, battery energy storage, and adjustments to heating systems would have on energy consumption. With a digital twin, such strategies can be modelled, allowing a view of how the network behaves and its performance under different scenarios.

Cutting through complexity

While digital twin technology for energy management has been under the spotlight for some time, its potential has yet to be fully realised. One reason for this is the perceived complexity of creating digital twins, with specific skills required to model complex processes and systems reliably. While it is true that specialist expertise is needed to initialise digital twins, ‘aftercare’ is much more easily managed.

Therefore, the initial complexity involved shouldn’t be regarded as a barrier, especially when specialists are available to build and provide the training required for organisations to manage responsibility for the twin after integration.

While sustainability is a hot topic right now, the value of digital twins for electrical systems in industrial settings extends much further. For example, the Electricity at Work Act makes specific references to the documentation requirements for all buildings, with single line diagrams an essential requirement. Despite this long-required aspect of buildings control, keeping these up to date, accessible, and to remain confident that they are a factual representation has always been challenging. This is again where the value of a proper digital twin is proven.

Building a model of the electrical system that is more easily updated and where elements and characteristics can be added makes it a powerful simulation tool and a reliable source of up-to-date information for other purposes. This negates the need for expensive and time-heavy data collection at intervals. With a digital twin there is one true view of electrical systems shared across projects, with contractors, for example, so everyone is working to a common framework.

The first step towards any goal is to gain visibility of your current state so that you can design impactful and measurable strategies. Digital tools provide the visibility needed to test-drive different routes in virtual surroundings, choosing which is most efficient for the real journey. We know that such sophisticated energy-management technology is already being used to power electric vehicles, which is only made possible by using digital twins. Electrical modelling of this type is still not commonplace in industry, despite obvious benefits.

The question is, why is this technology not being utilised when the benefits are already so clear, and the potential so vast? Whatever the reason for hesitancy, the urgency to answer sustainability targets must surely make digital twin technology worth serious consideration. If not now, then when?